The talk discusses the issue of finding suitable modelling approaches for capturing multicellular system dynamics. Computational models and tools envisioned by our group are presented. In particular the talk introduces (i) the Biochemical Tuple Spaces (BTS-SOC) coordination model adopted to simulate structured biochemical systems, (ii) MS-BioNET developed to efficiently simulate multi-compartment systems and (iii) ALCHEMIST developed for supporting chemical models of multi-compartment dynamic networks.
(Talk by Sara Montagna, CINI InfoLife, Pisa, Italy, 11/7/2014)
Systems biology is the computational and mathematical modeling of complex biological systems. It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach (holism instead of the more traditional reductionism) to biological research.
Berlin center for genome based bioinformatics koch05Slava Karpov
This document summarizes the research activities of the Berlin Center for Genome Based Bioinformatics at the Technical University of Applied Sciences. The center focuses on modeling and analyzing biochemical systems using Petri nets. Specifically, it has modeled central metabolic pathways like glycolysis and developed Petri net tools to validate biochemical networks and analyze the behavior of large networks like E. coli metabolism.
Systems biology aims to understand biological systems as a whole rather than individual parts. Early criticisms saw molecular biology as too reductionist. Systems modeling using mathematical approaches also emerged. Standards like SBML and community-building efforts were important to allow sharing and integration of computational models between different research groups and software tools. This helped a systems biology community flourish by providing interoperability between various modeling approaches and data types.
Introduction to Systemics with focus on Systems BiologyMrinal Vashisth
The core content discusses the terminology used in Systems Sciences, the systems thinking/approach or Systemics. Focus is kept on Systems Biology for the most part of the presentations where it is compared with other disciplines and examples of Systems Biology approach and challenges of systems science are also discussed.
The sad thing about uploading this to Slide Share is that animations don't work.
Computational Approaches to Systems BiologyMike Hucka
Presentation given at the Sydney Computational Biologists meetup on 21 August 2013 (http://australianbioinformatics.net/past-events/2013/8/21/computational-approaches-to-systems-biology.html).
This document discusses systems biology and some of its tools. It defines systems biology as the study of interactions between parts of biological systems to understand how they function. Biological networks involve interactions between pathways. Networks can be modeled as nodes and edges. Tools described for modeling and analyzing networks include Cytoscape for visualization, CellDesigner for drawing networks, and STRING for protein-protein interaction data. Databases of pathways, interactions and models are also listed.
1) Systems biology aims to understand biology at the system level rather than just individual components. This requires advanced modeling and data analysis techniques.
2) Challenges in systems biology include understanding complex relationships between components, dynamic behavior over time, and controlling systems with unknown functions.
3) Artificial intelligence can help address these challenges through techniques like machine learning, knowledge representation, and problem solving. It has already been applied to tasks like gene alignment modeling and phylogenetic inference.
Systems biology & Approaches of genomics and proteomicssonam786
This presentation provides the basic understanding of varous genomics and proteomics techniques.Systems biology studies life as a system .It includes the study of living system using various omic technologies .
Systems biology is the computational and mathematical modeling of complex biological systems. It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach (holism instead of the more traditional reductionism) to biological research.
Berlin center for genome based bioinformatics koch05Slava Karpov
This document summarizes the research activities of the Berlin Center for Genome Based Bioinformatics at the Technical University of Applied Sciences. The center focuses on modeling and analyzing biochemical systems using Petri nets. Specifically, it has modeled central metabolic pathways like glycolysis and developed Petri net tools to validate biochemical networks and analyze the behavior of large networks like E. coli metabolism.
Systems biology aims to understand biological systems as a whole rather than individual parts. Early criticisms saw molecular biology as too reductionist. Systems modeling using mathematical approaches also emerged. Standards like SBML and community-building efforts were important to allow sharing and integration of computational models between different research groups and software tools. This helped a systems biology community flourish by providing interoperability between various modeling approaches and data types.
Introduction to Systemics with focus on Systems BiologyMrinal Vashisth
The core content discusses the terminology used in Systems Sciences, the systems thinking/approach or Systemics. Focus is kept on Systems Biology for the most part of the presentations where it is compared with other disciplines and examples of Systems Biology approach and challenges of systems science are also discussed.
The sad thing about uploading this to Slide Share is that animations don't work.
Computational Approaches to Systems BiologyMike Hucka
Presentation given at the Sydney Computational Biologists meetup on 21 August 2013 (http://australianbioinformatics.net/past-events/2013/8/21/computational-approaches-to-systems-biology.html).
This document discusses systems biology and some of its tools. It defines systems biology as the study of interactions between parts of biological systems to understand how they function. Biological networks involve interactions between pathways. Networks can be modeled as nodes and edges. Tools described for modeling and analyzing networks include Cytoscape for visualization, CellDesigner for drawing networks, and STRING for protein-protein interaction data. Databases of pathways, interactions and models are also listed.
1) Systems biology aims to understand biology at the system level rather than just individual components. This requires advanced modeling and data analysis techniques.
2) Challenges in systems biology include understanding complex relationships between components, dynamic behavior over time, and controlling systems with unknown functions.
3) Artificial intelligence can help address these challenges through techniques like machine learning, knowledge representation, and problem solving. It has already been applied to tasks like gene alignment modeling and phylogenetic inference.
Systems biology & Approaches of genomics and proteomicssonam786
This presentation provides the basic understanding of varous genomics and proteomics techniques.Systems biology studies life as a system .It includes the study of living system using various omic technologies .
Introduction to Ontologies for Environmental BiologyBarry Smith
1. The document introduces ontologies for environmental biology and discusses several disciplines that could benefit from their use, including GIS, ecology, environmental biology, and various "-omics" fields.
2. It describes what an ontology is and compares ontologies to legends for maps or diagrams, which allow integration and help humans and computers make sense of complex data. Ontologies provide standardized terminology and annotations.
3. The document outlines the Open Biomedical Ontologies (OBO) Foundry, a collection of interoperable reference ontologies for annotating biomedical data. Foundry ontologies include the Gene Ontology and other ontologies for molecules, cells, anatomical structures, and more. They are developed through consensus and share
Sarah Daakour is a molecular biologist who earned her PhD in molecular biology from the University of Liege in Belgium. She has over 10 years of professional experience in protein signaling and interaction research. Her work has focused on identifying protein network perturbations in acute lymphoblastic leukemia and characterizing the tumor suppressor EXT-1 as a regulator of the Notch signaling pathway. She has published several journal articles and conference presentations on this topic.
Applied Bioinformatics & Chemoinformatics: Techniques, Tools, and OpportunitiesHezekiah Fatoki
The computational methods for in silico drug discovery have been broadly categories into two fields bioinformatics and chemoinformatics. In case of bioinformatics, major emphasis is on identification and validation of drug targets, mainly based on functional/structural annotation of genomes. In case of chemoinformatics or pharmacoinformatics, major emphasis is on designing of drug molecules or ligands and their interaction with drug targets.
WHAT IS BIOINFORMATICS?
Computational Biology/Bioinformatics is the application of computer sciences and allied technologies to answer the questions of Biologists, about the mysteries of life. It has evolved to serve as the bridge between:
Observations (data) in diverse biologically-related disciplines and
The derivations of understanding (information)
APPLICATIONS OF BIOINFORMATICS
Computer Aided Drug Design
Microarray Bioinformatics
Proteomics
Genomics
Biological Databases
Phylogenetics
Systems Biology
EMBL-EBI is a large bioinformatics resource based in Cambridge, UK. It provides freely available data and services for genomics, proteomics, transcriptomics and more. The presentation discusses EMBL-EBI's resources like Ensembl for genomics, UniProt for proteomics, and Reactome for pathways. It also covers standards and data integration efforts like DAS and PSICQUIC that allow different data sources to interoperate.
The European Bioinformatics Institute (EBI) is a center for bioinformatics research and services located in Hinxton, UK. EBI grew out of EMBL's work providing public biological databases and offers major databases on DNA, RNA, proteins, pathways, and more. EBI's website provides access to these databases as well as a variety of bioinformatics tools for sequence analysis, proteomics, microarrays, and more through different channels on their site.
The document discusses template-free modeling of protein structures. It explains that template-free modeling uses a library of protein fragments from known structures to explore possible structures for a query protein. The fragments are obtained from remote homologs that may share weak sequence similarity. The quality of predictions decreases for larger proteins due to the difficulty of conformational searching. The document concludes that new methods are needed to advance template-free protein structure prediction techniques.
Bioinformatics—an introduction for computer scientistsunyil96
The document introduces computer scientists to the field of bioinformatics. It provides a high-level overview of key concepts, including:
- Bioinformatics aims to develop computational models to complement biological experiments by helping interpret vast amounts of genomic data.
- A living cell can be described at the molecular level, with interactions between intracellular molecules controlled by shape, location, and reactions facilitated by enzymes.
- Computational techniques are needed to understand cell behavior from incomplete and noisy biological data, especially using evolutionary principles to extrapolate information across species.
Join us in Boston this coming Fall to attend Cambridge Healthtech Institute's (CHI) 2nd Annual FAST: Functional Analysis & Screening Technologies Congress on November 17-19, 2014 and meet with a community of 250+ biologists, screening managers, assay developers, engineers and pharmacologists dedicated to improving in vitro cell models and phenotypic screening to advance drug discovery and development at 6 conferences: Phenotypic Drug Discovery (Part I & II), Engineering Functional 3D Models, Screening and Functional Analysis of 3D Models, Organotypic Culture Models for Toxicology and Physiologically-Relevant Cellular Tumor Models for Drug Discovery. Delegates have the opportunity to share insights in interactive panel discussions and connect during networking breaks. View innovative technologies and scientific research revolutionizing early-stage drug discovery in the exhibit/poster hall.
Bioinformatics software tools can be classified into different categories like homology tools, sequence analysis tools, and protein functional analysis tools. These tools extract meaningful information from large datasets and allow users to compare protein sequences to databases to analyze protein functions. Examples of popular bioinformatics tools mentioned include BLAST, FASTA, EMBOSS, PROSPECT, RASMOL, and Pattern hunter. Bioinformatics projects that utilize these tools are also briefly outlined.
Free webinar-introduction to bioinformatics - biologist-1Elia Brodsky
The Omics Logic Introduction to Bioinformatics program is a one-month online training program that provides an introduction to the field of bioinformatics for beginners. The program consists of six sessions taught by an international team of experts, covering topics like genomics, transcriptomics, statistical analysis, machine learning, and a final bioinformatics project. Participants will learn data analysis skills in Python and R and how to extract insights from multi-omics datasets with applications in biomedicine. The goal is to prepare students for data-driven research in life sciences through interactive lessons, coding exercises, and independent projects.
Bioinformatics is the use of computers for storage, retrieval, manipulation, and distribution of information related to biological macromolecules such as DNA, RNA, and proteins. It involves developing computational tools and databases to analyze biological data. Key areas include sequence analysis, structural analysis, functional analysis, biological databases, sequence alignment, protein structure prediction, molecular phylogenetics, and genomics. The goals are to better understand living systems at the molecular level through computational analysis of biological data.
A collaborative model for bioinformatics education: combining biologically i...Elia Brodsky
Presented at the 6th Annual LA Conference on Computational Biology & Bioinformatics
Authors:
Kimberlee Mix*, Patricia Dorn*, Donald Hauber*, Scott McDermott**, Ryan Harvey** , Jack LeBien***, Sahil Sethi***, Julia Panov***, Avi Titievsky****, Elia Brodsky***
Departments of Biological Sciences*, Mathematics and Computer Science**, Loyola University New Orleans, 6363 St Charles Avenue, New Orleans, LA 70118
Pine Biotech, Inc***, 1441 Canal St. New Orleans, LA 70112
Tauber Bioinformatics Research Center****, University of Haifa Multi Purpose Building Room 225A Mount Carmel, Haifa 3498838 ISRAEL
Despite the growing impact of bioinformatics in the biological science community, integration of an on-site bioinformatics curriculum is cost prohibitive for many universities due to the necessary infrastructure and computational resources. Furthermore, many programs prioritize the technical aspects of bioinformatics over the biological concepts and logic of analyses, thus limiting the emphasis on critical thinking, problem solving, and in-depth inquiry. To address the gap in bioinformatics education and train students to approach complex biomedical problems, we present a new model for curriculum development that combines our unique online learning environment with traditional pedagogical approaches delivered through academic partnerships. The T-BioInfo platform (https://t-bio.info) allows users to combine computational analysis modules into pipelines to develop solutions for ‘omics data and machine learning problems. State-of-the-art tools for analysis, integration, and visualization of data are offered through a user-friendly interface. In parallel, online educational modules provide a theoretical framework for the analysis methods and experimental techniques. This model for bioinformatics training was implemented at Loyola University New Orleans, a liberal arts institution, for the first time in January 2018. Twelve undergraduate students and five faculty members participated in a new one-semester bioinformatics course. After completing a core set of online modules and pipelines, students conducted team research projects on topics such as patient derived xenograft (PDX) models, immune responses in cancer, and precision medicine. Gains in critical thinking and problem-solving skills were observed and participants were enthusiastic about engaging in bioinformatics research. In conclusion, our collaborative model for bioinformatics education combines best-practices in online and in-class learning with a powerful computational platform. This model could be implemented in undergraduate and graduate curricula to enhance research, build partnerships with industry, and strengthen the scientific workforce.
This dissertation developed algorithms and software tools to analyze the biological role of low complexity regions (LCRs) in proteins. It evaluated and improved methods for identifying homologs containing LCRs. It also created LCR-eXXXplorer, a web resource with unique tools for exploring annotated LCRs among millions of proteins. Using these tools, the dissertation predicted pathogenicity of E. coli strains based on genomic composition, showing prediction is possible with limited data like from metagenomic samples. The results open new areas for research on sequence search validation and large-scale experiments.
Louisiana Biomedical Research Network - Fall 2020 Bioinformatics Program Ove...Elia Brodsky
This document describes an online bioinformatics training platform called T-BioInfo that offers 16 hands-on bioinformatics courses and access to cloud tools. The courses cover topics such as genomics, transcriptomics, epigenomics, metagenomics, and data science for omics data. Student reviews praise the interactive nature and informative sessions of the program.
This document provides an overview of bioinformatics software. It discusses how bioinformatics is an interdisciplinary field that develops methods and tools for understanding biological data. The document outlines the history, goals, approaches, relation to other fields, and conclusion of bioinformatics. It was written by Umer Farooq for a class at the University of Education, Okara Campus in Pakistan.
Bioinformatics for beginners (exam point of view)Sijo A
. The term bioinformatics is coined by…………………………….
Paulien Hogeweg
2. What is an entry in database?
The process of entering data into a computerised database or spreadsheet.
3. Define BLASTp
BLAST- Basic Local Alignment Search Tool
It is a homology and similarity search tool.
It is provided by NCBI.
It is used to compare a query DNA sequence with a database of sequences.
4. What is Ecogenes?
Ecogene is a database and website and it is developed to improve structural and functional annotation of E.coli K-12 MG 1655.
Bioinformatics on the internet provides many resources and benefits. It allows for easy access and sharing of vast biological databases and genomic data. The internet facilitates collaboration between researchers globally and provides tools for storing, organizing, and analyzing biological information. Key resources available online include biological databases, software for data analysis, educational courses, journals, and tools for sequence analysis, structure prediction, and more. This expands the scope of bioinformatics and allows research to advance more rapidly through improved access to information and resources.
The document compares leadership to chemical reactions in a vessel. It suggests that effective leaders, like catalysts in chemical reactions, help employees find better paths to be productive with less energy. It also notes that great leaders understand not to stress employees, just as applying too much pressure to some reactants can lead to uncontrolled products. The metaphor of chemical reactions in a vessel provides new insights into understanding leadership.
An Agent-Based Approach to Pedestrian and Group Dynamics: Experimental and Re...Giuseppe Vizzari
The document presents a model for simulating pedestrian and crowd dynamics that considers the presence of groups. The model is an agent-based approach built on floor field cellular automata. It incorporates factors for group cohesion by adding a positive factor for movement towards nearby group members. The model is tested in simple counterflow scenarios and a real-world simulation of pedestrian flow at Hajj pilgrimage sites. Results show the model captures effects of groups like higher combined flows at high densities when groups form lines.
Introduction to Ontologies for Environmental BiologyBarry Smith
1. The document introduces ontologies for environmental biology and discusses several disciplines that could benefit from their use, including GIS, ecology, environmental biology, and various "-omics" fields.
2. It describes what an ontology is and compares ontologies to legends for maps or diagrams, which allow integration and help humans and computers make sense of complex data. Ontologies provide standardized terminology and annotations.
3. The document outlines the Open Biomedical Ontologies (OBO) Foundry, a collection of interoperable reference ontologies for annotating biomedical data. Foundry ontologies include the Gene Ontology and other ontologies for molecules, cells, anatomical structures, and more. They are developed through consensus and share
Sarah Daakour is a molecular biologist who earned her PhD in molecular biology from the University of Liege in Belgium. She has over 10 years of professional experience in protein signaling and interaction research. Her work has focused on identifying protein network perturbations in acute lymphoblastic leukemia and characterizing the tumor suppressor EXT-1 as a regulator of the Notch signaling pathway. She has published several journal articles and conference presentations on this topic.
Applied Bioinformatics & Chemoinformatics: Techniques, Tools, and OpportunitiesHezekiah Fatoki
The computational methods for in silico drug discovery have been broadly categories into two fields bioinformatics and chemoinformatics. In case of bioinformatics, major emphasis is on identification and validation of drug targets, mainly based on functional/structural annotation of genomes. In case of chemoinformatics or pharmacoinformatics, major emphasis is on designing of drug molecules or ligands and their interaction with drug targets.
WHAT IS BIOINFORMATICS?
Computational Biology/Bioinformatics is the application of computer sciences and allied technologies to answer the questions of Biologists, about the mysteries of life. It has evolved to serve as the bridge between:
Observations (data) in diverse biologically-related disciplines and
The derivations of understanding (information)
APPLICATIONS OF BIOINFORMATICS
Computer Aided Drug Design
Microarray Bioinformatics
Proteomics
Genomics
Biological Databases
Phylogenetics
Systems Biology
EMBL-EBI is a large bioinformatics resource based in Cambridge, UK. It provides freely available data and services for genomics, proteomics, transcriptomics and more. The presentation discusses EMBL-EBI's resources like Ensembl for genomics, UniProt for proteomics, and Reactome for pathways. It also covers standards and data integration efforts like DAS and PSICQUIC that allow different data sources to interoperate.
The European Bioinformatics Institute (EBI) is a center for bioinformatics research and services located in Hinxton, UK. EBI grew out of EMBL's work providing public biological databases and offers major databases on DNA, RNA, proteins, pathways, and more. EBI's website provides access to these databases as well as a variety of bioinformatics tools for sequence analysis, proteomics, microarrays, and more through different channels on their site.
The document discusses template-free modeling of protein structures. It explains that template-free modeling uses a library of protein fragments from known structures to explore possible structures for a query protein. The fragments are obtained from remote homologs that may share weak sequence similarity. The quality of predictions decreases for larger proteins due to the difficulty of conformational searching. The document concludes that new methods are needed to advance template-free protein structure prediction techniques.
Bioinformatics—an introduction for computer scientistsunyil96
The document introduces computer scientists to the field of bioinformatics. It provides a high-level overview of key concepts, including:
- Bioinformatics aims to develop computational models to complement biological experiments by helping interpret vast amounts of genomic data.
- A living cell can be described at the molecular level, with interactions between intracellular molecules controlled by shape, location, and reactions facilitated by enzymes.
- Computational techniques are needed to understand cell behavior from incomplete and noisy biological data, especially using evolutionary principles to extrapolate information across species.
Join us in Boston this coming Fall to attend Cambridge Healthtech Institute's (CHI) 2nd Annual FAST: Functional Analysis & Screening Technologies Congress on November 17-19, 2014 and meet with a community of 250+ biologists, screening managers, assay developers, engineers and pharmacologists dedicated to improving in vitro cell models and phenotypic screening to advance drug discovery and development at 6 conferences: Phenotypic Drug Discovery (Part I & II), Engineering Functional 3D Models, Screening and Functional Analysis of 3D Models, Organotypic Culture Models for Toxicology and Physiologically-Relevant Cellular Tumor Models for Drug Discovery. Delegates have the opportunity to share insights in interactive panel discussions and connect during networking breaks. View innovative technologies and scientific research revolutionizing early-stage drug discovery in the exhibit/poster hall.
Bioinformatics software tools can be classified into different categories like homology tools, sequence analysis tools, and protein functional analysis tools. These tools extract meaningful information from large datasets and allow users to compare protein sequences to databases to analyze protein functions. Examples of popular bioinformatics tools mentioned include BLAST, FASTA, EMBOSS, PROSPECT, RASMOL, and Pattern hunter. Bioinformatics projects that utilize these tools are also briefly outlined.
Free webinar-introduction to bioinformatics - biologist-1Elia Brodsky
The Omics Logic Introduction to Bioinformatics program is a one-month online training program that provides an introduction to the field of bioinformatics for beginners. The program consists of six sessions taught by an international team of experts, covering topics like genomics, transcriptomics, statistical analysis, machine learning, and a final bioinformatics project. Participants will learn data analysis skills in Python and R and how to extract insights from multi-omics datasets with applications in biomedicine. The goal is to prepare students for data-driven research in life sciences through interactive lessons, coding exercises, and independent projects.
Bioinformatics is the use of computers for storage, retrieval, manipulation, and distribution of information related to biological macromolecules such as DNA, RNA, and proteins. It involves developing computational tools and databases to analyze biological data. Key areas include sequence analysis, structural analysis, functional analysis, biological databases, sequence alignment, protein structure prediction, molecular phylogenetics, and genomics. The goals are to better understand living systems at the molecular level through computational analysis of biological data.
A collaborative model for bioinformatics education: combining biologically i...Elia Brodsky
Presented at the 6th Annual LA Conference on Computational Biology & Bioinformatics
Authors:
Kimberlee Mix*, Patricia Dorn*, Donald Hauber*, Scott McDermott**, Ryan Harvey** , Jack LeBien***, Sahil Sethi***, Julia Panov***, Avi Titievsky****, Elia Brodsky***
Departments of Biological Sciences*, Mathematics and Computer Science**, Loyola University New Orleans, 6363 St Charles Avenue, New Orleans, LA 70118
Pine Biotech, Inc***, 1441 Canal St. New Orleans, LA 70112
Tauber Bioinformatics Research Center****, University of Haifa Multi Purpose Building Room 225A Mount Carmel, Haifa 3498838 ISRAEL
Despite the growing impact of bioinformatics in the biological science community, integration of an on-site bioinformatics curriculum is cost prohibitive for many universities due to the necessary infrastructure and computational resources. Furthermore, many programs prioritize the technical aspects of bioinformatics over the biological concepts and logic of analyses, thus limiting the emphasis on critical thinking, problem solving, and in-depth inquiry. To address the gap in bioinformatics education and train students to approach complex biomedical problems, we present a new model for curriculum development that combines our unique online learning environment with traditional pedagogical approaches delivered through academic partnerships. The T-BioInfo platform (https://t-bio.info) allows users to combine computational analysis modules into pipelines to develop solutions for ‘omics data and machine learning problems. State-of-the-art tools for analysis, integration, and visualization of data are offered through a user-friendly interface. In parallel, online educational modules provide a theoretical framework for the analysis methods and experimental techniques. This model for bioinformatics training was implemented at Loyola University New Orleans, a liberal arts institution, for the first time in January 2018. Twelve undergraduate students and five faculty members participated in a new one-semester bioinformatics course. After completing a core set of online modules and pipelines, students conducted team research projects on topics such as patient derived xenograft (PDX) models, immune responses in cancer, and precision medicine. Gains in critical thinking and problem-solving skills were observed and participants were enthusiastic about engaging in bioinformatics research. In conclusion, our collaborative model for bioinformatics education combines best-practices in online and in-class learning with a powerful computational platform. This model could be implemented in undergraduate and graduate curricula to enhance research, build partnerships with industry, and strengthen the scientific workforce.
This dissertation developed algorithms and software tools to analyze the biological role of low complexity regions (LCRs) in proteins. It evaluated and improved methods for identifying homologs containing LCRs. It also created LCR-eXXXplorer, a web resource with unique tools for exploring annotated LCRs among millions of proteins. Using these tools, the dissertation predicted pathogenicity of E. coli strains based on genomic composition, showing prediction is possible with limited data like from metagenomic samples. The results open new areas for research on sequence search validation and large-scale experiments.
Louisiana Biomedical Research Network - Fall 2020 Bioinformatics Program Ove...Elia Brodsky
This document describes an online bioinformatics training platform called T-BioInfo that offers 16 hands-on bioinformatics courses and access to cloud tools. The courses cover topics such as genomics, transcriptomics, epigenomics, metagenomics, and data science for omics data. Student reviews praise the interactive nature and informative sessions of the program.
This document provides an overview of bioinformatics software. It discusses how bioinformatics is an interdisciplinary field that develops methods and tools for understanding biological data. The document outlines the history, goals, approaches, relation to other fields, and conclusion of bioinformatics. It was written by Umer Farooq for a class at the University of Education, Okara Campus in Pakistan.
Bioinformatics for beginners (exam point of view)Sijo A
. The term bioinformatics is coined by…………………………….
Paulien Hogeweg
2. What is an entry in database?
The process of entering data into a computerised database or spreadsheet.
3. Define BLASTp
BLAST- Basic Local Alignment Search Tool
It is a homology and similarity search tool.
It is provided by NCBI.
It is used to compare a query DNA sequence with a database of sequences.
4. What is Ecogenes?
Ecogene is a database and website and it is developed to improve structural and functional annotation of E.coli K-12 MG 1655.
Bioinformatics on the internet provides many resources and benefits. It allows for easy access and sharing of vast biological databases and genomic data. The internet facilitates collaboration between researchers globally and provides tools for storing, organizing, and analyzing biological information. Key resources available online include biological databases, software for data analysis, educational courses, journals, and tools for sequence analysis, structure prediction, and more. This expands the scope of bioinformatics and allows research to advance more rapidly through improved access to information and resources.
The document compares leadership to chemical reactions in a vessel. It suggests that effective leaders, like catalysts in chemical reactions, help employees find better paths to be productive with less energy. It also notes that great leaders understand not to stress employees, just as applying too much pressure to some reactants can lead to uncontrolled products. The metaphor of chemical reactions in a vessel provides new insights into understanding leadership.
An Agent-Based Approach to Pedestrian and Group Dynamics: Experimental and Re...Giuseppe Vizzari
The document presents a model for simulating pedestrian and crowd dynamics that considers the presence of groups. The model is an agent-based approach built on floor field cellular automata. It incorporates factors for group cohesion by adding a positive factor for movement towards nearby group members. The model is tested in simple counterflow scenarios and a real-world simulation of pedestrian flow at Hajj pilgrimage sites. Results show the model captures effects of groups like higher combined flows at high densities when groups form lines.
This document provides an introduction to complex systems and agent-based modeling. It discusses what complex systems are, including examples ranging from simple systems of a few agents to more sophisticated systems involving many agents. Complex systems are characterized as having emergent behaviors that arise from the interactions of the agents following simple rules, without any centralized control. The document also provides examples of complex systems in nature, such as pattern formation, neural networks, swarm intelligence in insect colonies, collective motion of flocking and schooling, and social biological systems.
ABM Interactions: Engaging Your Target Accounts Where They AreTerminus
This document discusses account-based marketing (ABM) interactions and strategies. It begins by providing statistics about marketing and sales effectiveness. It then outlines the typical customer journey from awareness to purchase. The document proposes identifying the best-fit accounts, focusing on engaging people in similar roles, using the right content and channels, and turning customers into advocates. It presents examples of high-tech and high-touch vs low-tech and low-touch interactions. Finally, it discusses three ABM interaction strategies focused on demand generation, pipeline velocity, and up-selling/cross-selling, outlining the relevant stakeholders, strategies, interactions, and success metrics for each.
This reaction paper analyzes theories of first language acquisition from chapters one and two. It summarizes different approaches from behaviorism, nativism, and functionalism. While each perspective provides insights, the author argues an integrated approach considering psychology, anthropology, and linguistics best explains the complex process of how children acquire language. The paper also discusses implications for teaching English as a second language.
The document provides guidance on writing a response paper, which involves critically analyzing a text by summarizing its key ideas, stating an opinion on part of the text, and supporting that opinion with evidence from the text. It outlines the steps to writing a good response paper, which include reading the text twice to understand the main topic and author's argument, forming opinions on the text's claims and evidence, drafting a summary, and writing a first draft of the response paper expressing agreement, disagreement, or evaluation of the text's strengths and weaknesses. The document also reviews methods for paraphrasing texts, such as changing vocabulary, verb forms, word classes, and synthesizing information.
The document discusses technology integration in the classroom. It outlines two learning theories that provide a foundation for integration: directed and constructivist models. It also discusses the Technology Integration Plan (TIP) model for planning effective classroom technology use. The chapter emphasizes that certain conditions must be present for successful integration, including a clear technology vision, policies for safe internet use, technical support, and effective teaching strategies. Overall, the key takeaways are that technology integration requires planning, support structures, and strategies to enhance teaching and learning.
The document discusses several theories of first language acquisition:
1) Behaviourism views language as learned through stimulus-response and imitation, though it does not explain why all humans acquire language while other species do not.
2) The cognitive approach sees innate cognitive abilities as influencing language learning beyond just environmental factors. Piaget's stages of development also related to language acquisition.
3) The nativist approach, proposed by Chomsky, argues humans are born with an innate language acquisition device and universal grammar containing basic language structures. This explains consistent language acquisition across environments.
4) While each theory provides some insights, the document concludes that both innate and environmental factors likely influence language acquisition in a gradual process,
Leader's Guide to Motivate People at WorkWeekdone.com
To motivate employees, leaders should provide more praise, attention, responsibility, and incentives. Specifically, leaders should recognize employees' good work, keep employees informed about company goals and strategies, assign more challenging tasks with autonomy, establish incentive programs with realistic yet challenging goals, and provide pay raises correlated with employee performance and development. Leaders can use a performance management tool like Weekdone to understand employee status, provide transparent feedback, and align goals across different levels.
This paper explores the complex field of synthetic biology, including its historical roots, guiding ideas, contemporary uses, and moral dilemmas raised by its groundbreaking discoveries.
The document describes Carlos Manuel Estévez-Bretón's doctoral research on functionally characterizing metabolic networks. The goals are to classify metabolic pathways based solely on their functional features using machine learning methods, develop a system for functionally representing metabolic networks, and apply machine learning methods to study systems biology in new ways. The methodology involves using data from MetaCyc and KEGG databases, developing a functional representation model, classifying networks with supervised and unsupervised machine learning methods, and evaluating the results using various metrics.
Tales from BioLand - Engineering Challenges in the World of Life SciencesStefano Di Carlo
Prof. Alfredo Benso from SysBio Group @ Politecnico di Torino keynote presentation at ICIIBMS - IEEE International Conference on Intelligent Informatics and BioMedical Sciences, on Nov 26 2017 in Okinawa (Japan).
This document discusses the concept of morphogenetic engineering, which aims to design artificial self-organized systems capable of developing elaborate architectures without central planning. It begins by looking at natural complex systems like animal flocking and termite mounds that self-organize. The focus is on "architectures without architects" in biological systems. Morphogenetic engineering is proposed as a new type of engineering that designs self-organizing agents, not the architectures directly, taking inspiration from embryogenesis, simulated development and synthetic biology. Several research projects are summarized that aim to model biological development and create modular, programmable artificial self-construction.
2011-10-11 Open PHACTS at BioIT World Europeopen_phacts
The document discusses the Innovative Medicines Initiative's Open PHACTS project, which aims to develop robust standards and apply them in a semantic integration platform ("Open Pharmacological Space") to integrate drug discovery data from various public and private sources. The project brings together partners from industry, academia, and non-profits to build an open infrastructure for linking drug discovery knowledge and supporting ongoing research. It outlines the technical approach, priorities, and initial progress on developing exemplar applications and a prototype "lash up" system.
This document introduces machine learning techniques and their applications in systems biology. It discusses the challenges in systems biology due to the complexity and size of biological systems. Machine learning is well-suited for systems biology as it can analyze large datasets, adapt to new information, and discover relationships hidden in data. Specifically, the document describes inductive logic programming, clustering, Bayesian networks, and decision trees and how they are used in classification, forecasting, clustering, description, deviation detection, link analysis, and visualization of biological data.
The document provides an introduction to systems biology. It begins with an overview of what systems biology is, including definitions that emphasize studying biological functions and mechanisms through signal and system-oriented approaches. It then discusses why systems biology is used, including to better understand biological systems as a whole rather than individual parts, and to aid in areas like drug development. The document also covers common techniques in systems biology, such as modeling biological networks and integrating different types of data. It concludes by listing some examples of case studies where systems biology has been applied, including for metabolic and gene regulatory network modeling.
The document summarizes a computational modeling approach for simulating synthetic microbial biofilms at a multiscale level. The approach combines 3D biophysical models of individual cells with models of genetic regulation and intercellular signaling. It was implemented in a software tool called CellModeller that uses parallel GPU computing to simulate over 30,000 cells in a typical biofilm colony within 30 minutes. Simulation results reproduced key features of experimentally observed E. coli biofilm colony morphologies. The modeling framework provides a way to predict the behavior of synthetic biofilms prior to experimental construction.
International Journal of Biometrics and Bioinformatics(IJBB) Volume (3) Issue...CSCJournals
This document summarizes a research paper that proposes a new crossover operator called Sequential Constructive Crossover (SCX) for solving the Traveling Salesman Problem (TSP) using a genetic algorithm. SCX constructs offspring from parent chromosomes by selecting better edges present in the parents while maintaining the node sequence. The performance of SCX is compared to other crossover operators like Edge Recombination Crossover and Generalized N-point Crossover on benchmark TSP instances, and experimental results show that SCX finds higher quality solutions than the other operators. The TSP is an NP-complete problem where the goal is to find the shortest route to visit all cities on a tour and return to the starting city. Genetic algorithms are
Three's a crowd-source: Observations on Collaborative Genome AnnotationMonica Munoz-Torres
It is impossible for a single individual to fully curate a genome with precise biological fidelity. Beyond the problem of scale, curators need second opinions and insights from colleagues with domain and gene family expertise, but the communications constraints imposed in earlier applications made this inherently collaborative task difficult. Apollo, a client-side, JavaScript application allowing extensive changes to be rapidly made without server round-trips, placed us in a position to assess the difference this real-time interactivity would make to researchers’ productivity and the quality of downstream scientific analysis. To evaluate this, we trained and supported geographically dispersed scientific communities (hundreds of scientists and agreed-upon gatekeepers, in ~100 institutions around the world) to perform biologically supported manual annotations, and monitored their findings. We observed that: 1) Previously disconnected researchers were more productive when obtaining immediate feedback in dialogs with collaborators. 2) Unlike earlier genome projects, which had the advantage of more highly polished genomes, recent projects usually have lower coverage. Therefore curators now face additional work correcting for more frequent assembly errors and annotating genes that are split across multiple contigs. 3) Automated annotations were improved as exemplified by discoveries made based on revised annotations, for example ~2800 manually annotated genes from three species of ants granted further insight into the evolution of sociality in this group, and ~3600 manual annotations contributed to a better understanding of immune function, reproduction, lactation and metabolism in cattle. 4) There is a notable trend shifting from whole-genome annotation to annotation of specific gene families or other gene groups linked by ecological and evolutionary significance. 5) The distributed nature of these efforts still demand strong, goal-oriented (i.e. publication of findings) leadership and coordination, as these are crucial to the success of each project. Here we detail these and other observations on collaborative genome annotation efforts.
An approach for self creating software code in bionets with artificial embryo...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Synthetic biology is an emerging scientific field that combines engineering and biology to design and construct novel biological systems or redesign existing natural biological systems. The document provides a brief history of synthetic biology from 1960 to 2013, highlighting key developments such as the first synthetic genetic circuits in 2000-2003 and the engineering of metabolic pathways. It also discusses topics such as standard biological parts, modeling and design techniques, applications in health, energy and environment, as well as potential risks that need consideration with the further development of the field.
Eko Artificial Life, Determinacy of Ecological Resilience and Classification ...ijtsrd
Simulating the effects of biotic and a biotic interactions with or without human interference to compute ecological resilience within a closed ecosystem. Simulating a set food chain in the said ecosystem and studying the effects of biotic factors on the biotic chains and vice versa. Classifying and comparing various closed ecosystems on the said parameters and determinacy of the stability of an ecosystem over time. Study of various a biotic compound statistics via graphical representations in a time controlled order. Ability to introduce new species, remove existing ones or change the concentration amounts of current biotic parameters and thus study various results in a cause effect relationship. Time factoring and control over biotic gene pool to affect ecosystems on both a macro and micro scale. In depth latency about ecosystems in the gaming industry, weather simulators, and life perseverance of various endangered and threatened species along with sustainable resource control. Ankita Dhillon | Kirti Bhatia | Rohini Sharma "Eko: Artificial Life, Determinacy of Ecological Resilience and Classification of Closed Ecosystems" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd46318.pdf Paper URL: https://www.ijtsrd.com/computer-science/bioinformatics/46318/eko-artificial-life-determinacy-of-ecological-resilience-and-classification-of-closed-ecosystems/ankita-dhillon
1. This study explored the molecular mechanisms of drought tolerance in ryegrass varieties by integrating transcriptomics, proteomics, and metabolomics approaches.
2. The study identified differentially expressed metabolites, proteins, and transcripts in response to drought stress between a drought-resistant and susceptible ryegrass variety.
3. Methods included transcriptome sequencing, qRT-PCR, mass spectrometry, gas chromatography–mass spectrometry to analyze changes at the transcript, protein, and metabolite levels under drought conditions between the two varieties. This integrative omics analysis provided insights into drought tolerance mechanisms.
Web Apollo: Lessons learned from community-based biocuration efforts.Monica Munoz-Torres
This presentation tries to highlight the importance and relevance of community-based curation of biological data. It describes the results of harvesting expertise from dispersed researchers assigning functions to predicted and curated peptides, as well as collaborative efforts for standardization of genes and gene product attributes across species and databases.
This document summarizes the relationship between systems biology and theoretical physics. It discusses how systems biology combines experimental techniques with mathematical modeling to understand biological processes, and how this field draws from both engineering and physics approaches. While engineering aims to numerically simulate biological systems, physics seeks universal principles and laws. The document reviews how concepts from physics, like statistical physics and nonlinear dynamics, have influenced systems biology research and how further integrating theoretical physics perspectives could aid understanding of biological systems.
The document discusses bioinformatics and metagenomics. It provides an overview of bioinformatics, describing how it uses tools and algorithms to analyze high-throughput biological data. It then discusses metagenomics, which involves directly sequencing environmental DNA without culturing to study microbial communities. Metagenomics projects have revealed that less than 0.5% of DNA in environments represents known organisms, and it provides thousands of new gene families.
AN OPTIMIZATION ALGORITHM BASED ON BACTERIA BEHAVIORijaia
Paradigms based on competition have shown to be useful for solving difficult problems. In this paper we present a new approach for solving hard problems using a collaborative philosophy. A collaborative philosophy can produce paradigms as interesting as the ones found in algorithms based on a competitive philosophy. Furthermore, we show that the performance - in problems associated to explosive combinatorial - is comparable to the performance obtained using a classic evolutive approach.
Talk by J. Eisen for NZ Computational Genomics meetingJonathan Eisen
This document discusses phylogeny-driven approaches to studying microbial diversity using ribosomal RNA gene sequences. It provides background on how advances in sequencing technology and appreciation of microbial diversity have enabled microbiome research. The document outlines several uses of phylogeny in microbiome studies, including constructing species phylogenies using rRNA sequences and assigning taxonomy to environmental sequences via rRNA phylotyping. It describes challenges with analyzing large rRNA datasets and introduces an automated pipeline called STAP that generates high-quality multiple sequence alignments and phylogenetic trees to classify sequences and analyze species diversity in a manner that scales to large datasets.
Measuring Trustworthiness in Neuro-Symbolic IntegrationAndrea Omicini
This document discusses measuring trustworthiness in neuro-symbolic integration systems. It begins by providing background on neuro-symbolic integration systems and how they integrate neural and symbolic AI approaches. It then discusses the public and regulatory focus on ensuring the trustworthiness of AI systems. The document motivates the need to define metrics to measure how well neuro-symbolic systems meet requirements for trustworthy AI, as requirements alone may not be enough without metrics. It proposes exploring how to translate and measure compliance with requirements for areas like human oversight, robustness, and privacy in the context of neuro-symbolic systems.
Explainable Pervasive Intelligence with Self-explaining AgentsAndrea Omicini
Pervasiveness of ICT resources along with the promise of ubiquitous intelligence is pushing hard both our demand and our fears of AI: demand mandates for the ability to inject intelligence ubiquitously; fears compel the behaviour of intelligent systems to be observable, explainable, and accountable. Whereas the first wave of the new "AI Era" was mostly heralded by sub-symbolic approaches, features like explainability are better provided by symbolic techniques. In particular, the notion of explanation should be regarded as a core notion for intelligent systems, rather than just an add-on to make them understandable to humans. Based on symbolic AI techniques to match intuitive and rational cognition, explanation should then be regarded as a fundamental tool for inter-agent communication among heterogeneous intelligent agents in open multi-agent systems. More generally, self-explaining agents should work as the basic components in the engineering of intelligent systems integrating both symbolic and sub-/non-symbolic AI techniques.
On the Integration of Symbolic and Sub-symbolic – Explaining by DesignAndrea Omicini
The more intelligent systems based on sub-symbolic techniques pervade our everyday lives, the less human can understand them. This is why symbolic approaches are getting more and more attention in the general effort to make AI interpretable, explainable, and trustable. Understanding the current state of the art of AI techniques integrating symbolic and sub-symbolic approaches is then of paramount importance, nowadays—in particular in the XAI perspective. In this talk we first provides an overview of the main symbolic/sub-symbolic integration techniques, focussing in particular on those targeting explainable AI systems. Then we expand the notion of “explainability by design” to the realm of multi-agent systems, where XAI techniques can play a key role in the engineering of intelligent systems.
Not just for humans: Explanation for agent-to-agent communicationAndrea Omicini
Once precisely defined so as to include just the explanation’s act, the notion of explanation should be regarded as a central notion in the engineering of intelligent system—not just as an add-on to make them understandable to humans. Based on symbolic AI techniques to match intuitive and rational cognition, explanation should be exploited as a fundamental tool for inter-agent communication among heterogeneous agents in open multi-agent systems. More generally, explanation-ready agents should work as the basic components in the engineering of intelligent systems integrating both symbolic and sub-/non-symbolic AI techniques.
Presented by Andrea Omicini @ AIxIA 2020 Discussion Paper Workshop
Blockchain for Intelligent Systems: Research PerspectivesAndrea Omicini
We summarise and compare features of MAS and BCT, and discuss how they could be fruitfully integrated in the engineering of intelligent systems by adopting a long-term research perspective.
Injecting (Micro)Intelligence in the IoT: Logic-based Approaches for (M)MASAndrea Omicini
Pervasiveness of ICT resources along with the promise of ubiquitous intelligence is pushing hard both our demand and our fears of AI: demand mandates for the ability to inject (micro) intelligence ubiquitously, fears compel the behaviour of intelligent systems to be observable, explainable, and accountable.
Whereas the first wave of the new "AI Era" was mostly heralded by non-symbolic approaches, features like explainability are better provided by symbolic techniques.
In this talk we focus on logic-based approaches, and discuss their potential in pervasive scenarios like the IoT and open (M)MAS along with our latest results in the field.
Andrea Omicini, Roberta Calegari
Invited Talk
MMAS 2018, Stockholm, Sweden, 14 July 2018
Conversational Informatics: From Conversational Systems to Communication Inte...Andrea Omicini
The document discusses the history and development of conversational systems. It outlines some of the early work in natural language dialogue systems from the 1960s and focuses on three main areas of research: understanding and generating stories, cognitive systems, and integration of these approaches. Current conversational systems aim to more fully integrate these areas to provide more human-like conversational abilities.
Complexity in computational systems: the coordination perspectiveAndrea Omicini
In this talk we discuss the role of coordination models and technologies in the engineering of complex computational systems.
Complex Systems Physics Meeting IMT-UNIBO
Dipartimento di Fisica e Astronomia, Università di Bologna
Bologna, Italy, 15/02/2018
Nature-inspired Coordination: Current Status and Research TrendsAndrea Omicini
Tutorial @WI 2017, Leipzig, 23 August 2017
Andrea Omicini & Stefano Mariani, Lecturers
Originating from closed parallel systems, coordination models and technologies gained in expressive power so as to deal with complex distributed systems. In particular, nature-inspired models of coordination emerged in the last decade as the most effective approaches to tackle the complexity of pervasive, intelligent, and self-* systems.
In the first part of the tutorial we introduce the basic notions of coordination and coordination model, and relate them to the notions of interaction and complexity. Then, the most relevant nature-inspired coordination (NIC) models are discussed, along with their relationship with the many facets of tuple-based models. In the third part we discuss the main open issues and explore the trends for future development of NIC. Finally, as a case study, we focus on MoK (Molecules of Knowledge), a NIC model for knowledge self-organisation, where data and information autonomously aggregate and spread toward knowledge prosumers.
Novel Opportunities for Tuple-based Coordination: XPath, the Blockchain, and ...Andrea Omicini
The increasing maturity of some well-established technologies – such as XPath – along with the sharp rise of brand-new ones – i.e. the blockchain – presents new opportunities to researchers in the field of multi-agent coordination. In this talk we briefly discuss a few technologies which, once suitably interpreted and integrated, have the potential to impact the very roots of tuple-based coordination as it stems from the archetypal LINDA model.
Micro-intelligence for the IoT: Teaching the Old Logic Dog New Programming Tr...Andrea Omicini
New application scenarios for pervasive intelligent systems open novel perspectives for logic-based approaches, in particular when coupled with agent-based technologies and methods. In this explorative talk we provide some examples of how logic programming and its extensions can work as sources of micro-intelligence for the IoT, at both the individual and the collective level, along with an overall architectural view of IoT systems exploiting logic-based technologies.
Logic Programming as a Service (LPaaS): Intelligence for the IoTAndrea Omicini
Talk @ ICNSC 2017, Calabria, Italy, 16 May 2017
Abstract: The widespread diffusion of low-cost computing devices, such as Arduino boards and Raspberry Pi, along with improvements of Cloud computing platforms, are paving the way towards a whole new set of opportunities for Internet of Things (IoT) applications and services. Varying degrees of intelligence are often required for supporting adaptation and self-management—yet, they should be provided in a light-weight, easy to use and customise, highly-interoperable way. Accordingly, in this paper we explore the idea of Logic Programming as a Service (LPaaS) as a novel and promising re-interpretation of distributed logic programming in the IoT era. After introducing the reference context and motivating scenarios of LPaaS as a key enabling technology for intelligent IoT, we define the LPaaS general system architecture. Then, we present a prototype implementation built on top of the tuProlog system, which provides the required interoperability and customisation. We showcase the LPaaS potential through a case study designed as a simplification of the motivating scenarios.
Privacy through Anonymisation in Large-scale Socio-technical Systems: The BIS...Andrea Omicini
Large-scale socio-technical systems (STS) inextricably inter-connect individual – e.g., the right to privacy –, social – e.g., the effectiveness of organisational processes –, and technology issues —e.g., the software engineering process. As a result, the design of the complex software infrastructure involves also non-technological aspects such as the legal ones—so that, e.g., law-abidingness can be ensured since the early stages of the software engineering process. By focussing on contact centres (CC) as relevant examples of knowledge-intensive STS, we elaborate on the articulate aspects of anonymisation: there, individual and organisational needs clash, so that only an accurate balancing between legal and technical aspects could possibly ensure the system efficiency while preserving the individual right to privacy. We discuss first the overall legal framework, then the general theme of anonymisation in CC. Finally we overview the technical process developed in the context of the BISON project.
Project presentation @ DMI, Università di Catania, Italy, 25 July 2016
The impact of mobile technologies on healthcare is particularly evident in the case of self-management of chronic diseases, where they can decrease spending and improve the patient quality of life. In this talk we propose the adoption of agent-based modelling and simulation techniques as built-in tools to dynamically monitor patient health state and provide feedbacks for self-management. To demonstrate the feasibility of our proposal we focus on Type 1 Diabetes Mellitus as our case study, and provide some preliminary simulation results.
Game Engines to Model MAS: A Research RoadmapAndrea Omicini
This document outlines a research roadmap for bridging the gap between multi-agent systems (MAS) and game engines (GE). It finds that while GEs excel at modeling environments, they provide weak support for agency and sociality as conceptualized in MAS. The roadmap proposes a "mirror worlds" approach where GEs represent environments and MAS handle autonomy and social interaction. A case study applies this by implementing the dining philosophers problem in Unity3D, with agents, chairs and a table modeled as game objects that coordinate through messaging. The roadmap concludes that pursuing GE-based MAS infrastructure could integrate the technologies' strengths while avoiding forcing either to handle responsibilities it is not meant for.
Open distributed multi-agent systems featuring autonomous components demand coordination mechanisms for both functional and non-functional properties. Heterogeneity of requirements regarding interaction means and paradigms, stemming from the diverse nature of components, should not affect the effectiveness of coordination. Along this line, in this paper we share our pragmatical experience in the integration of objective and subjective, synchronous and asynchronous, reactive and pro-active coordination approaches within two widely-adopted agent-oriented technologies (JADE and Jason), enabling coordinating components to dynamically adapt their interaction means based on static preference or run-time contingencies.
Towards Logic Programming as a Service: Experiments in tuPrologAndrea Omicini
The document discusses experiments with logic programming as a service (LPaaS) using tuProlog. It proposes an LPaaS architecture with local APIs for creating engines, loading theories, and querying. It also describes implementing tuProlog as a service (2PaaS) on iOS, where tuProlog is embedded in an app and provides an API via URL schemes for other apps to interface with it. Example application scenarios are presented, including using tuProlog for symbolic derivatives and multi-language programming. Further work is outlined to better define and extend the LPaaS paradigm.
The document discusses the concept of space in computer science and computational systems. It describes how physical distribution of computational units and communication channels creates virtual spaces, such as distributed systems and middleware environments. It emphasizes that situated distributed systems and pervasive computing systems are needed to handle computation in physical environments and take into account the spatial aspects of those environments. Situatedness and context-awareness are important properties for computational systems to exhibit as they become more immersed in physical space.
Introductory tutorial on the foundations of agents and multi-agent systems at the 18th European Agent Systems Summer School (EASSS 2016) – 25 July 2016, Catania, Italy
Academic Publishing in the Digital Era: A Couple of Issues (Open Access—Well,...Andrea Omicini
The document discusses issues with the current academic publishing system. It notes that while technology has made production, diffusion, and access to scholarly works negligible in cost, access to most literature remains expensive. It also distinguishes between the validation of research, which ensures quality, and evaluation, which occurs after publication. While new publishers and self-archiving aim to address costs, true validation requires peer review before rather than after publication to maintain standards and scale effectively. Overall reforms are needed to make the system more economically sustainable while maintaining scientific rigor.
Most important New features of Oracle 23c for DBAs and Developers. You can get more idea from my youtube channel video from https://youtu.be/XvL5WtaC20A
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
8 Best Automated Android App Testing Tool and Framework in 2024.pdfkalichargn70th171
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfVALiNTRY360
Salesforce Healthcare CRM, implemented by VALiNTRY360, revolutionizes patient management by enhancing patient engagement, streamlining administrative processes, and improving care coordination. Its advanced analytics, robust security, and seamless integration with telehealth services ensure that healthcare providers can deliver personalized, efficient, and secure patient care. By automating routine tasks and providing actionable insights, Salesforce Healthcare CRM enables healthcare providers to focus on delivering high-quality care, leading to better patient outcomes and higher satisfaction. VALiNTRY360's expertise ensures a tailored solution that meets the unique needs of any healthcare practice, from small clinics to large hospital systems.
For more info visit us https://valintry360.com/solutions/health-life-sciences
UI5con 2024 - Boost Your Development Experience with UI5 Tooling ExtensionsPeter Muessig
The UI5 tooling is the development and build tooling of UI5. It is built in a modular and extensible way so that it can be easily extended by your needs. This session will showcase various tooling extensions which can boost your development experience by far so that you can really work offline, transpile your code in your project to use even newer versions of EcmaScript (than 2022 which is supported right now by the UI5 tooling), consume any npm package of your choice in your project, using different kind of proxies, and even stitching UI5 projects during development together to mimic your target environment.
E-Invoicing Implementation: A Step-by-Step Guide for Saudi Arabian CompaniesQuickdice ERP
Explore the seamless transition to e-invoicing with this comprehensive guide tailored for Saudi Arabian businesses. Navigate the process effortlessly with step-by-step instructions designed to streamline implementation and enhance efficiency.
WWDC 2024 Keynote Review: For CocoaCoders AustinPatrick Weigel
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...Crescat
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
Everything You Need to Know About X-Sign: The eSign Functionality of XfilesPr...XfilesPro
Wondering how X-Sign gained popularity in a quick time span? This eSign functionality of XfilesPro DocuPrime has many advancements to offer for Salesforce users. Explore them now!
E-commerce Development Services- Hornet DynamicsHornet Dynamics
For any business hoping to succeed in the digital age, having a strong online presence is crucial. We offer Ecommerce Development Services that are customized according to your business requirements and client preferences, enabling you to create a dynamic, safe, and user-friendly online store.
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
UI5con 2024 - Bring Your Own Design SystemPeter Muessig
How do you combine the OpenUI5/SAPUI5 programming model with a design system that makes its controls available as Web Components? Since OpenUI5/SAPUI5 1.120, the framework supports the integration of any Web Components. This makes it possible, for example, to natively embed own Web Components of your design system which are created with Stencil. The integration embeds the Web Components in a way that they can be used naturally in XMLViews, like with standard UI5 controls, and can be bound with data binding. Learn how you can also make use of the Web Components base class in OpenUI5/SAPUI5 to also integrate your Web Components and get inspired by the solution to generate a custom UI5 library providing the Web Components control wrappers for the native ones.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Oracle Database 19c New Features for DBAs and Developers.pptx
Agent-based and Chemical-inspired Approaches for Multicellular Models
1. Agent-based and Chemical-inspired Approaches for
Multicellular Models
Sara Montagna, Andrea Omicini and Mirko Viroli
sara.montagna@unibo.it
Alma Mater Studiorum—Universit`a di Bologna a Cesena
Workshop on Multicellular Systems Biology
Laboratorio CINI InfoLife
Pisa, Italy, 11th July 2014
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 1 / 45
2. Motivation and Concepts
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 2 / 45
3. Motivation and Concepts Biological Background
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 3 / 45
4. Motivation and Concepts Biological Background
Multicellular Systems
Multicellular systems are living organisms that are composed of numerous
interacting cells...1
Immune System
Neural System
Embryogenesis
Adult Stem Cells
Tumor Growth
...
1
www.nature.com
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 4 / 45
5. Motivation and Concepts Biological Background
Levels of Biological Organisation2
2
[DWMC11]
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 5 / 45
6. Motivation and Concepts Biological Background
Multicellular Systems
Biological systems are inherently of multi-scale nature
Global emergent behaviour by mechanisms happening across multiple
space and time scales
Each scale integrates information from strata above and below
upward and downward causation
Interactions among components are the building block for the vast
majority of mechanisms at each level
Three hierarchical scale for multicellular systems [Set12]
Molecular, cellular and tissue
Intracellular regulatory network controls molecular mechanisms
gene expression, receptor activity and protein degradation
Individual cell decides on its next developmental step,
proliferation, fate determination and motility
Cell population acts in concert to develop its anatomy and function
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 6 / 45
7. Motivation and Concepts Biological Background
On the Morphogenesis of Living Systems
Developmental Biology researches the mechanisms of development,
differentiation, and growth in animals and plants at the molecular, cellular,
and genetic levels.
Animal developmental steps
1 Fertilisation of one egg
2 Mitotic division
3 Cellular differentiation
4 Morphogenesis
control of the organised spatial distribution of the cell diversity
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 7 / 45
8. Motivation and Concepts Requirements
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 8 / 45
9. Motivation and Concepts Requirements
Multicellular Systems Biology
Focus of research in systems biology is shifting from intracellular
studies towards studies of whole cells or populations of cells
→ Multicellular Systems Biology
Middle-out approach (nor bottom-up neither top-down)
it starts with an intermediate scale (the cell, the basic unit of life) and
it is gradually expanded to include both smaller and larger scales
It requires multiple data
molecular data such as gene expression profiles
image data such as spatial-temporal growth pattern
Figure: [DM11]
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 9 / 45
10. Motivation and Concepts Requirements
A Computational Model for Addressing these Scenarios
Computational model requirements
1 Multi-scale
for spamming several spatial and temporal scales
for reproducing the intra- and inter-scale interactions and integration
2 Diffusion / Transfer
for studying the effects of short and long range signals
for modelling the compartment membrane
3 Stochasticity
for capturing the aleatory behaviour characteristic of those systems
involving few entities
4 Dynamic topology
for modelling the compartment division and movement
5 Heterogeneity
for modelling individual structures and behaviours of different entities
of the biological system
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 10 / 45
11. Motivation and Concepts Related Work
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 11 / 45
12. Motivation and Concepts Related Work
Looking around...
Recently the trend of research strongly moved towards Multicellular
Systems Biology. Many research groups:
DRESDEN — Research group multiscale modelling of multicellular
systems3
INRIA / IZBI Joint Research Group — Multicellular systems biology4
SPECIAL ISSUE — Multiscale Modeling and Simulation in Computational
Biology – deadline 30th September 2014 5
ESMTB — Multi-scale modeling platforms in multicellular systems
biology6, symposium at the European Conference on Mathematical and
Theoretical Biology
3
http://tu-dresden.de/
4
http://ms.izbi.uni-leipzig.de
5
http://www.mdpi.com/journal/computation/special_issues/multiscale-model
6
http://www.math.chalmers.se/~torbjrn/ECMTB/Minisymposium/no3.pdf
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 12 / 45
13. Motivation and Concepts Related Work
Brief Survey on Multi-scale Methods
The interdependent nature of multicellular processes often makes it
difficult to apply standard mathematical techniques to separate out the
scales, uncouple the physical processes or average over contributions from
discrete components.[CO13]
Over the past decades several multi-scale methods developed [DM11]
Quasi continuum method, Hybrid quantum mechanics-molecular
mechanics methods, Equation free multi-scale methods, Coarse
projective integration, Gap-tooth scheme, Patch dynamic,
Heterogeneus multi-scale method, Agent-based modelling, complex
automata
Some of these applied in biology
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 13 / 45
14. Motivation and Concepts Related Work
Brief Survey on Multi-scale Frameworks
Chaste — An open source C++ library for computational physiology and
biology
CompuCell3D — Modelling tissue formation
EPISIM Platform — Graphical multi-scale modeling and simulation of
multicellular systems
CellSys — Modular software for physics-based tissue modelling in 3D
VirtualLeaf — Towards an off-lattice Cellular Potts model
Biocellion — Accelerating multicellular biological simulation
Morpheus — User-friendly modeling of multicellular systems
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 14 / 45
15. Motivation and Concepts Related Work
Brief Survey on Related Work in Modelling Morphogenesis
Main modelling attempts
[GJK+04] — continuous mathematical model based on a set of coupled
nonlinear reaction-diffusion Partial Differential Equations
√
protein synth./degr., gene inhibition and activation, protein diffusion
x notion of compartments, stochasticity
[CHC+05] — combines discrete methods based on cellular-automata and
continuous models based on reaction-diffusion equation
√
interacting compartments (agents), protein diffusion
x realistic model for cell internal behaviour
[LIDP10] — stochastic model of reaction-diffusion systems
√
protein diffusion
x gene interactions, protein synth./degr., cellular divisions
...
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 15 / 45
16. Our Modelling Approach
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 16 / 45
17. Our Modelling Approach Biochemical Tuple Spaces (BTS-SOC)
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 17 / 45
18. Our Modelling Approach Biochemical Tuple Spaces (BTS-SOC)
The coordination model approach
Base idea
Coordination models explicitly deal with interaction in comp. sys.
Simulation frameworks based on coordination are well-suited for the
simulation of a complex system
as a special sort of multiagent-based simulation (MABS)
Nature-inspired coordination tuple-based models are the most
promising ones for the simulation of biological systems [Omi13]
Goals
Experimenting the expressive power of coordination models in the
simulation of molecular and cellular systems
Empowering the environment as a first-class abstraction by the notion
of tuple spaces
tuple-spaces are the coordination abstractions as shared distributed
spaces, used by agents to synchronise, cooperate, and coordinate
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 18 / 45
19. Our Modelling Approach Biochemical Tuple Spaces (BTS-SOC)
Biochemical Tuple spaces for Self-Organising Coordination
Computational model
Based on BTS-SOC [VC09]
tuple space working as a compartment where biochemical reactions
take place as coordination laws
which are actually stochastic
chemical reactants are represented as tuples
the environment has a structure – requiring a notion of locality, and
allowing components of any sort to move through a topology
Simulation infrastructure
Biochemical tuple spaces are built as ReSpecT tuple centres
Simulations run upon a TuCSoN distributed coordination middleware
Tuples are logic-based tuples
Biochemical laws are implemented as ReSpecT specification tuples
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 19 / 45
20. Our Modelling Approach Biochemical Tuple Spaces (BTS-SOC)
A First Modelling Attempt [GPOS13]
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 20 / 45
21. Our Modelling Approach MS-BioNET
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 21 / 45
22. Our Modelling Approach MS-BioNET
Ad-hoc Framework to Tackle Scenarios of Dev. Bio.
MS-BioNet
Naturally supporting scenarios with many compartments
Use state-of-the-art implem. techniques for the simulation engine
Ground on Gillespie’s characterisation of chemistry as CTMC
A module for parameter tuning
Parameter tuning as an optimisation problem
searching the solution with metaheuristics
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 22 / 45
23. Our Modelling Approach MS-BioNET
MS-BioNet
MS-BioNet’s Conceptual levels [MV10]
1 Computational Model: graph of compartments, with transfer reactions
2 Surface Language: systems as logic-oriented description programs
system structure
inner chemical behaviours
3 Simulation Engine: implementation of Gillespie SSA [Gil77]
reproducing the exact chemical evolution/diffusion of substances
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 23 / 45
24. Our Modelling Approach Alchemist : An Hybrid Approach
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 24 / 45
25. Our Modelling Approach Alchemist : An Hybrid Approach
Alchemist simulation approach
Base idea
Start from the existing work with stochastic chemical systems
simulation
Extend it as needed to model multi-compartment dynamic networks
Goals
Full support for Continuous Time Markov Chains (CTMC)
Rich environments with mobile nodes, etc.
More expressive reactions
Fast and flexible SSA engine
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 25 / 45
26. Our Modelling Approach Alchemist : An Hybrid Approach
Enriching the environment description
Environment
Node
Reactions
Molecules
Alchemist world
The Environment contains and links together Nodes
Each Node is programmed with a set of Reactions
Nodes contain Molecules
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 26 / 45
27. Our Modelling Approach Alchemist : An Hybrid Approach
Extending the concept of reaction
From a set of reactants that combine themselves in a set of products to:
Number of
neighbors<3
Node
contains
something
Any other
condition
about this
environment
Rate equation: how conditions
influence the execution speed
Conditions Probability distribution Actions
Any other
action
on this
environment
Move a node
towards...
Change
concentration
of something
Reaction
In Alchemist, every event is an occurrence of a Reaction
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 27 / 45
28. Our Modelling Approach Alchemist : An Hybrid Approach
Dynamic Engine: Making efficient SSA Algorithms more
flexible
Existing SSA algorithms
Several versions, but same base schema [Gil77]:
1 Select next reaction to execute according to the markovian rates
2 Execute it
3 Update the markovian rates which may have changed
Very efficient versions exist such as [GB00]
What they miss is what we added
Reactions can be added and removed during the simulation
Support for non-exponential time distributed events (e.g. triggers)
Dependencies among reactions are evaluated considering their
“context”, speeding up the update phase
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 28 / 45
29. Our Modelling Approach Alchemist : An Hybrid Approach
Alchemist Architecture: it is fully modular
Environment
User Interface
Alchemist language
Application-specific Alchemist Bytecode Compiler
Environment description in application-specific language
Incarnation-specific language
Reporting System
Interactive UI
Reaction Manager
Dependency Graph
Core Engine
Simulation Flow Language Parser
Environment Instantiator
XML Bytecode
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 29 / 45
30. Experiments
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 30 / 45
31. Experiments
On the Drosophila Melanogaster Morphogenesis
Overview until Cleavage Cycle 14 temporal class 8
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 31 / 45
32. Experiments
The Model
Taking in mind our Drosophila case study. . .
Goal of the model
Reproducing the expression pattern of the gap genes at Cl. Cyc. 14
from the fertilised egg
Validation over acquired images from the FlyEx database a
a
http://flyex.ams.sunysb.edu/flyex/index.jsp
Model components
Whole embryo as a 2D continuous cell
Environment composed by fixed nodes filled with morphogens
Nuclei/Cells as mobile nodes able to
1 divide
2 migrate
3 interact via diffusing morphogens
4 host gene expression regulation
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 32 / 45
33. Experiments
The cell compartment
Each cellular process is modeled as a chemical like reaction with rate r
Cellular division
condition maximum number of other cells in the neighbourhood
action create a new cell
Cellular movement as a repulsion force
condition position of cells in the neighborhood
action move in a new position
Morphogen diffusion
condition morphogen a in node N
action morphogen a moved in node N1 ∈ neighbourhood(N)
Gene a regulation
condition tr. factor (act) / tr. factor + gene a product (inhib)
action tr. factor + gene a product (act) / tr. factor (inhib)
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 33 / 45
34. Experiments
Simulation Results at the Cl. Cyc 14 tc 8: Cell Divisions
Simulations are conducted over the Alchemist platform
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 34 / 45
35. Experiments
Qualitative Simulation Results at the Cl. Cyc 14 tc 8
Figure: Gap gene expressions: hb
(yellow), kni (red), gt (blue), Kr
(green)
Figure: The experimental data for
the expression of (from the top)
hb, kni, gt, Kr c Maria
Samsonova and John Reinitz
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 35 / 45
37. Supplementary Info
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 37 / 45
38. Supplementary Info
Projects we are/were in ...
1 SAPERE – Self-aware Pervasive Service Ecosystems
2010–2013
EU Seventh Framework Programme (7FP), FP7-ICT-2009.8.5:
Self-awareness in Autonomic Systems
Official Site: http://www.sapere-project.eu/
2 GALILEO – Ricostruzione e modellazione delle dinamiche molecolari e
genetiche alla base della precoce regionalizzazione degli embrioni di
zebrafish e di seaurchin
2009–2010
Funding Body: Universit`a Italo-Francese – Project Galileo 2008/2009
Official Site: http:
//apice.unibo.it/xwiki/bin/view/Projects/GalileoNETSCALE
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 38 / 45
39. Supplementary Info
Our Products
1 Alchemist
Alchemist is now open source, GPL licensed, and the whole code base
is publicly accessible on bitbucket
Official Site: alchemist.apice.unibo.it
2 MS-BioNET – MultiScale-Biochemical NETwork
Official Site: ms-bionet.apice.unibo.it
3 TuCSoN – Tuple Centres Spread over the Network
Official Site: tucson.apice.unibo.it
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 39 / 45
40. Future Work
Outline
1 Motivation and Concepts
Biological Background
Requirements
Related Work
2 Our Modelling Approach
Biochemical Tuple Spaces (BTS-SOC)
MS-BioNET
Alchemist : An Hybrid Approach
3 Experiments
4 Supplementary Info
5 Future Work
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 40 / 45
41. Future Work
Objective of our research in Developmental Biology
Provide an adequate simulation framework
full-feature computational model and simulator engine
virtual embryo
application at systems that present nowadays open questions
obtain a better understanding of some features of the system
verify hypothesis and theories underlying the model that try to explain
the system behaviour
make prediction to be tested by in-vivo experiments
ask what if questions about real system
H2020 calls – PERSONALISING HEALTH AND CARE
PHC-02-2015: Understanding disease: systems medicine
PHC-28-2015: Self management of health and disease and decision
support systems based on predictive computer modelling used by the
patient him or herself
PHC-30-2015: Digital representation of health data to improve
disease diagnosis and treatment
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 41 / 45
42. References
References I
Trevor M. Cickovski, Chengbang Huang, Rajiv Chaturvedi, Tilmann Glimm, H. George E.
Hentschel, Mark S. Alber, James A. Glazier, Stuart A. Newman, and Jes?s A. Izaguirre.
A framework for three-dimensional simulation of morphogenesis.
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2:273–288, 2005.
Jonathan Cooper and James Osborne.
Connecting models to data in multiscale multicellular tissue simulations.
Procedia Computer Science, 18(0):712 – 721, 2013.
2013 International Conference on Computational Science.
Joseph O. Dada and Pedro Mendes.
Multi-scale modelling and simulation in systems biology.
Integr. Biol., 3:86–96, 2011.
Thomas S. Deisboeck, Zhihui Wang, Paul Macklin, and Vittorio Cristini.
Multiscale cancer modeling.
Annual Review of Biomedical Engineering, 13:127–155, 2011.
M. A. Gibson and J. Bruck.
Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many
Channels.
The Journal of Physical Chemistry A, 104(9):1876–1889, March 2000.
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 42 / 45
43. References
References II
Daniel T. Gillespie.
Exact stochastic simulation of coupled chemical reactions.
Journal of Physical Chemistry, 81(25):2340–2361, December 1977.
Vitaly V. Gursky, Johannes Jaeger, Konstantin N. Kozlov, John Reinitz, and Alexander M.
Samsonov.
Pattern formation and nuclear divisions are uncoupled in drosophila segmentation:
comparison of spatially discrete and continuous models.
Physica D: Nonlinear Phenomena, 197(3-4):286–302, October 2004.
Pedro Pablo Gonz´alez P´erez, Andrea Omicini, and Marco Sbaraglia.
A biochemically-inspired coordination-based model for simulating intracellular signalling
pathways.
Journal of Simulation, 7(3):216–226, August 2013.
Special Issue: Agent-based Modeling and Simulation.
Paola Lecca, Adaoha E. C. Ihekwaba, Lorenzo Dematt´e, and Corrado Priami.
Stochastic simulation of the spatio-temporal dynamics of reaction-diffusion systems: the
case for the bicoid gradient.
J. Integrative Bioinformatics, 7(1), 2010.
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 43 / 45
44. References
References III
Sara Montagna and Mirko Viroli.
A framework for modelling and simulating networks of cells.
Electr. Notes Theor. Comput. Sci., 268:115–129, December 2010.
Proceedings of the 1st International Workshop on Interactions between Computer Science
and Biology (CS2Bio’10).
Andrea Omicini.
Nature-inspired coordination for complex distributed systems.
In Giancarlo Fortino, Costin Badica, Michele Malgeri, and Rainer Unland, editors,
Intelligent Distributed Computing VI, volume 446 of Studies in Computational Intelligence,
pages 1–6. Springer Berlin Heidelberg, 2013.
Yaki Setty.
Multi-scale computational modeling of developmental biology.
Bioinformatics, 28(15):2022–2028, 2012.
Mirko Viroli and Matteo Casadei.
Biochemical tuple spaces for self-organising coordination.
In John Field and Vasco T. Vasconcelos, editors, Coordination Languages and Models,
volume 5521 of LNCS, pages 143–162. Springer, Lisbon, Portugal, June 2009.
11th International Conference (COORDINATION 2009), Lisbon, Portugal, June 2009.
Proceedings.
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 44 / 45
45. References
Agent-based and Chemical-inspired Approaches for
Multicellular Models
Sara Montagna, Andrea Omicini and Mirko Viroli
sara.montagna@unibo.it
Alma Mater Studiorum—Universit`a di Bologna a Cesena
Workshop on Multicellular Systems Biology
Laboratorio CINI InfoLife
Pisa, Italy, 11th July 2014
Montagna (UNIBO) Alchemist/ABM for BIO CINI InfoLife 45 / 45