This document summarizes a presentation about automatic annotation in UniProtKB. It discusses how UniProtKB uses automatic annotation systems like UniRule and SAAS to annotate the increasing number of sequences as manual annotation cannot keep pace. UniRule allows manual creation of annotation rules while SAAS uses machine learning. It also describes how UniProtKB defines and works to annotate complete proteomes from various organisms.
UniProt is a large life sciences database that uses several ontologies like the Gene Ontology, keywords, taxonomy, and pathways to provide consistent navigation and aggregation of its data on protein sequences, functions, and features. The document discusses how ontologies help organize UniProt's large amount of data and provide benefits like auto-completion, set-oriented views, and potential for automation. It also seeks feedback on which additional data from UniProt could be organized through more detailed ontologies.
1. The document discusses how the concept of "keeping up with the Joneses" and arms races contributed to World War 1. It instructs students to take notes on how the industrial revolution enabled arms races between European powers and how this escalating military spending ultimately led to World War 1.
2. Students are asked to graph military spending data, define an arms race, draw connections to keeping up with neighbors, and predict which countries would lose in a European war.
3. The document provides guidance for an assignment analyzing the links between arms races, nationalism, and the outbreak of World War 1.
This document provides an overview of monopolies and monopoly markets. It begins with a bellringer asking questions about monopolies. It then defines a monopoly as a market with a single dominant seller and notes that monopolies have high barriers to entry. It discusses types of monopolies including geographic, government-granted, and technological monopolies. It provides examples of different types of monopolies. The document discusses price discrimination in monopoly markets and consumer and producer surplus. It closes with questions about why economists worry about monopolies and why technological monopolies are allowed to exist.
FLSS vuole essere un supporto tecnologico alla gestione della vita condivisa, semplice, giocoso e facile da usare, volto a rendere piacevole e formativo quel periodo della vita in cui giovani studenti e lavoratori condividono un appartamento, soprattutto nelle grandi città dove i canoni d'affitto sono molto alti.
Relationship of Metabolic syndrome and cognitive impairment has been discussed. Metabolic causes of Dementia and their reversibility has been discussed.
http://globalvision.com.vn/vn/wincor-nixdorf-b-36.htm
Wincor Nixdorf
Wincor Nixdorf là công ty của Đức một hãng hàng đầu thế giới về cung cấp thiết bị POS, giải pháp và dịch vụ IT cho ngành bán lẻ và ngân hàng. Các giải pháp phần cứng cũng chư phần mềm của Wincor hiệu quả cao với giá cả hợp lý, giúp tăng tốc và hiệu quả trong các ứng dụng ngân hàng (banking) và hệ thống bán lẻ (retail industries). Hiện Wincor Nixdorf đã hiện diện ở trên 100 nước, trong đó 41 nước có văn phòng đại diện. Với hơn 9,000 nhân viên trên toàn thế giới.
Financial Institutions, Merchants, and the Race Against CyberthreatsEMC
This Aite analyst report examines the common threats facing financial institutions and retailers, including mobile attacks, DDoS, and malware, and offers recommendations on common defenses deployed by players in both industries.
UniProt is a large life sciences database that uses several ontologies like the Gene Ontology, keywords, taxonomy, and pathways to provide consistent navigation and aggregation of its data on protein sequences, functions, and features. The document discusses how ontologies help organize UniProt's large amount of data and provide benefits like auto-completion, set-oriented views, and potential for automation. It also seeks feedback on which additional data from UniProt could be organized through more detailed ontologies.
1. The document discusses how the concept of "keeping up with the Joneses" and arms races contributed to World War 1. It instructs students to take notes on how the industrial revolution enabled arms races between European powers and how this escalating military spending ultimately led to World War 1.
2. Students are asked to graph military spending data, define an arms race, draw connections to keeping up with neighbors, and predict which countries would lose in a European war.
3. The document provides guidance for an assignment analyzing the links between arms races, nationalism, and the outbreak of World War 1.
This document provides an overview of monopolies and monopoly markets. It begins with a bellringer asking questions about monopolies. It then defines a monopoly as a market with a single dominant seller and notes that monopolies have high barriers to entry. It discusses types of monopolies including geographic, government-granted, and technological monopolies. It provides examples of different types of monopolies. The document discusses price discrimination in monopoly markets and consumer and producer surplus. It closes with questions about why economists worry about monopolies and why technological monopolies are allowed to exist.
FLSS vuole essere un supporto tecnologico alla gestione della vita condivisa, semplice, giocoso e facile da usare, volto a rendere piacevole e formativo quel periodo della vita in cui giovani studenti e lavoratori condividono un appartamento, soprattutto nelle grandi città dove i canoni d'affitto sono molto alti.
Relationship of Metabolic syndrome and cognitive impairment has been discussed. Metabolic causes of Dementia and their reversibility has been discussed.
http://globalvision.com.vn/vn/wincor-nixdorf-b-36.htm
Wincor Nixdorf
Wincor Nixdorf là công ty của Đức một hãng hàng đầu thế giới về cung cấp thiết bị POS, giải pháp và dịch vụ IT cho ngành bán lẻ và ngân hàng. Các giải pháp phần cứng cũng chư phần mềm của Wincor hiệu quả cao với giá cả hợp lý, giúp tăng tốc và hiệu quả trong các ứng dụng ngân hàng (banking) và hệ thống bán lẻ (retail industries). Hiện Wincor Nixdorf đã hiện diện ở trên 100 nước, trong đó 41 nước có văn phòng đại diện. Với hơn 9,000 nhân viên trên toàn thế giới.
Financial Institutions, Merchants, and the Race Against CyberthreatsEMC
This Aite analyst report examines the common threats facing financial institutions and retailers, including mobile attacks, DDoS, and malware, and offers recommendations on common defenses deployed by players in both industries.
RSA Monthly Online Fraud Report -- October 2013EMC
This document discusses cyber security awareness and how consumer online behaviors can put them at risk. It summarizes statistics from a survey of over 14,500 consumers in over 170 countries that found most consumers frequently engage in online activities like online banking, shopping, emailing and social media use. However, many consumers could improve their awareness and protection of their identity and information by updating anti-virus software more and checking credit reports more often. The document encourages readers to visit a website for more information on an online identity risk calculator.
This document provides examples of mathematical equations and calculations. It includes expressions with variables, multiplication, division, exponents, and equals signs. The document works through several arithmetic steps to solve for unknown values.
This document contains instructions and materials for a Latin American history lesson on independence movements. It includes discussion questions, reading assignments on the prelude to revolution and revolts in Mexico and South America, and an individual assignment to create a timeline with years of independence for various Latin American countries and the US, including flags or maps. It also asks how Latin Americans were influenced by Enlightenment ideas.
Software Defined Data Center: The Intersection of Networking and StorageEMC
There has been quite a bit of marketing rhetoric around Software Defined Data Center (SDDC) since VMware’s acquisition of Nicira. In this session we explore the components of a SDDC. Our specific focus is on the composition of a SDDC’s resource model: Compute, Networking, and Storage. The emphasis is on the disaggregated I/O for Network and Storage resources.
Objective 1: Describe the disaggregated I/O resource model employed to facilitate the use of virtualized Ethernet and Block devices in a Software Defined Data Center.
After this session you will be able to:
Objective 2: Explain how end-user driven provisioning of virtual Ethernet devices and Block devices serve to decouple resource use from infrastructure management.
Objective 3: Describe some of the opportunities and challenges associated with employing disaggregate I/O.
This document provides an overview of electrophoresis techniques. It defines electrophoresis as a method used to separate macromolecules like proteins based on their charge, size, and shape under the influence of an electric field. There are two main types - moving boundary electrophoresis where components separate in solution, and zone electrophoresis where separation occurs on a supporting medium like a gel or paper. Key factors that affect electrophoretic mobility and separation include the electric field strength, characteristics of the sample, properties of the supporting medium, and buffer composition and pH. Common electrophoresis methods include isoelectric focusing, high-voltage electrophoresis, capillary electrophoresis, and continuous versus discontinuous gel systems.
This document discusses concepts of elasticity and inelasticity of demand. It provides examples of goods and their likely responsiveness to price changes, from very elastic demands like video games to more inelastic demands like necessities. The document also discusses why firms and governments consider elasticity, with elastic goods having more responsive quantities to price changes for firms and inelastic goods sometimes having price controls from governments.
The document provides an overview of Streamlined Task Orientated Management of Projects (STOMP), a high-level project methodology designed to provide visibility of project processes. It discusses common project phases including planning, design, build, test, and delivery. STOMP sits above detailed methodologies to allow all resources to understand the process. Key aspects covered include the project plan, change control process, and tracking progress against the schedule. The goal is to enable teams to communicate project status easily to management.
FIRM: Capability-based Inline Mediation of Flash BehaviorsEMC
This paper presents a system that enforces finer-grained access control on a Flash application and its hosting web page. The approach embeds an inline reference monitor (IRM) within the hosting page and mediates the interactions between the DOM objects and Flash applications. It can be deployed without making any changes to browsers.
This document discusses the concept of price discrimination. It begins by defining price discrimination as selling the same good at different prices to different buyers based on their willingness to pay. It provides examples such as student/senior discounts and differences in airline ticket prices. The document explains that under perfect price discrimination, a monopolist can capture all consumer surplus as profit and eliminate deadweight loss. However, in reality firms can only imperfectly discriminate by dividing customers into groups based on observable traits related to willingness to pay. It concludes by asking questions about whether price discrimination should always be illegal and discussing the "Soup Nazi" character from Seinfeld.
This document provides an overview of Renaissance art and key concepts about the Renaissance period from the 1300s to 1550. It discusses causes of the Renaissance like the rediscovery of Greek/Roman ideas and art. Renaissance art is characterized by elements like perspective, realism, contrast between light and dark, and depicting humanism in Greek/Roman styles. The document lists and shows images of famous Renaissance artists like Michelangelo, Donatello, Da Vinci, and Raphael and some of their iconic works. Students are assigned a task analyzing Renaissance paintings or creating original art in the Renaissance style.
This document discusses features learned in Toy Task 3, including adding hyperlinks, custom animations, and slide shows. It covers applying slide layouts, inserting video and objects, adding simple animations and motion, and using word art. The goal is to replicate the information in this PPT document.
The document discusses work-life balance and its importance. It defines work-life balance as the perfect integration between work and life without interference. Poor work-life balance can lead to stress, physical problems, relational problems, decreased performance, and disturbed families. Achieving work-life balance requires planning work, providing flexibility, effective communication, organizational culture, stress management, and time management. Both organizations and employees must work together to develop strategies to help attain work-life balance.
MAGNE Consulting is headquartered in Kolkata and provides business transformation and process excellence advisory services to small and medium retail businesses. It helps clients align their people, processes, and technology using the IDAIM model to improve agility. Services include workshops, website design, digital marketing, creating standard operating procedures, audits, customer programs, and IT project management. MAGNE has successfully implemented transformations for various clients.
UniProt is a comprehensive, freely accessible database that is a central repository for protein data. It is produced through collaboration between the European Bioinformatics Institute, Swiss Institute of Bioinformatics, and Protein Information Resource. UniProt contains protein sequences, functional information, evolutionary data, and details about biological processes, post-translational modifications, interactions, and subcellular locations to characterize proteins.
UniProt is a comprehensive, freely accessible database that is a central repository for protein data. It is produced through collaboration between the European Bioinformatics Institute, Swiss Institute of Bioinformatics, and Protein Information Resource. UniProt contains protein sequences, functional information, evolutionary data, and details about biological processes, post-translational modifications, interactions, and subcellular locations to characterize proteins.
We all must do whatever is in our hands to prevent all kinds of cancer, which is the cause of millions of deaths every year. Work on your health-related presentations with the help of these editable Google Slides and PowerPoint templates.
Designing a community resource - Sandra OrchardEMBL-ABR
The document discusses designing a new community resource called the Complex Portal to describe protein complexes. It emphasizes conducting user studies, using community standards to enable data sharing and tool interoperability, and obtaining community input to ensure the resource meets researcher needs. Standards like PSI-MI and controlled vocabularies allow the resource to integrate data from other sources and enable sophisticated searches. Outreach is important to establish the resource as the primary reference.
Bioinformatics is the application of Information technology to store, organize and analyze the vast amount of biological data which is available in the form of sequences and structures of proteins and nucleic acids. The biological information of nucleic acids is available as sequences while the data of proteins is available as sequences and structures.
A biological database is a collection of data that is organized so that its contents can easily be accessed, managed, and updated. The activity of preparing a database can be divided in to:
Collection of data in a form which can be easily accessed
Making it available to a multi-user system (always available for the user)
An integrated publicly accessible bioinformatics resource to support genomic/proteomic research and scientific discovery.
Established in 1984, by the National Biomedical Research Foundation (NBRF) Georgetown University Medial Center, Washington D.C., USA.
It is the source of annotated protein databases and analysis tools for the researchers.
Serve as primary resource for the exploration of protein information.
Accessible by text search for entry and list retrieval, and also BLAST search and peptide match.
The National Center for Biomedical Ontology (NCBO) provides several software tools to enable semantically aware applications. These include BioPortal, an online library of biomedical ontologies, Ontology Widgets which allow integration of ontologies into websites, and the Annotator, a web service that semantically tags text with ontology terms. The NCBO also plans to develop a comprehensive index of online biomedical resources.
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.
RSA Monthly Online Fraud Report -- October 2013EMC
This document discusses cyber security awareness and how consumer online behaviors can put them at risk. It summarizes statistics from a survey of over 14,500 consumers in over 170 countries that found most consumers frequently engage in online activities like online banking, shopping, emailing and social media use. However, many consumers could improve their awareness and protection of their identity and information by updating anti-virus software more and checking credit reports more often. The document encourages readers to visit a website for more information on an online identity risk calculator.
This document provides examples of mathematical equations and calculations. It includes expressions with variables, multiplication, division, exponents, and equals signs. The document works through several arithmetic steps to solve for unknown values.
This document contains instructions and materials for a Latin American history lesson on independence movements. It includes discussion questions, reading assignments on the prelude to revolution and revolts in Mexico and South America, and an individual assignment to create a timeline with years of independence for various Latin American countries and the US, including flags or maps. It also asks how Latin Americans were influenced by Enlightenment ideas.
Software Defined Data Center: The Intersection of Networking and StorageEMC
There has been quite a bit of marketing rhetoric around Software Defined Data Center (SDDC) since VMware’s acquisition of Nicira. In this session we explore the components of a SDDC. Our specific focus is on the composition of a SDDC’s resource model: Compute, Networking, and Storage. The emphasis is on the disaggregated I/O for Network and Storage resources.
Objective 1: Describe the disaggregated I/O resource model employed to facilitate the use of virtualized Ethernet and Block devices in a Software Defined Data Center.
After this session you will be able to:
Objective 2: Explain how end-user driven provisioning of virtual Ethernet devices and Block devices serve to decouple resource use from infrastructure management.
Objective 3: Describe some of the opportunities and challenges associated with employing disaggregate I/O.
This document provides an overview of electrophoresis techniques. It defines electrophoresis as a method used to separate macromolecules like proteins based on their charge, size, and shape under the influence of an electric field. There are two main types - moving boundary electrophoresis where components separate in solution, and zone electrophoresis where separation occurs on a supporting medium like a gel or paper. Key factors that affect electrophoretic mobility and separation include the electric field strength, characteristics of the sample, properties of the supporting medium, and buffer composition and pH. Common electrophoresis methods include isoelectric focusing, high-voltage electrophoresis, capillary electrophoresis, and continuous versus discontinuous gel systems.
This document discusses concepts of elasticity and inelasticity of demand. It provides examples of goods and their likely responsiveness to price changes, from very elastic demands like video games to more inelastic demands like necessities. The document also discusses why firms and governments consider elasticity, with elastic goods having more responsive quantities to price changes for firms and inelastic goods sometimes having price controls from governments.
The document provides an overview of Streamlined Task Orientated Management of Projects (STOMP), a high-level project methodology designed to provide visibility of project processes. It discusses common project phases including planning, design, build, test, and delivery. STOMP sits above detailed methodologies to allow all resources to understand the process. Key aspects covered include the project plan, change control process, and tracking progress against the schedule. The goal is to enable teams to communicate project status easily to management.
FIRM: Capability-based Inline Mediation of Flash BehaviorsEMC
This paper presents a system that enforces finer-grained access control on a Flash application and its hosting web page. The approach embeds an inline reference monitor (IRM) within the hosting page and mediates the interactions between the DOM objects and Flash applications. It can be deployed without making any changes to browsers.
This document discusses the concept of price discrimination. It begins by defining price discrimination as selling the same good at different prices to different buyers based on their willingness to pay. It provides examples such as student/senior discounts and differences in airline ticket prices. The document explains that under perfect price discrimination, a monopolist can capture all consumer surplus as profit and eliminate deadweight loss. However, in reality firms can only imperfectly discriminate by dividing customers into groups based on observable traits related to willingness to pay. It concludes by asking questions about whether price discrimination should always be illegal and discussing the "Soup Nazi" character from Seinfeld.
This document provides an overview of Renaissance art and key concepts about the Renaissance period from the 1300s to 1550. It discusses causes of the Renaissance like the rediscovery of Greek/Roman ideas and art. Renaissance art is characterized by elements like perspective, realism, contrast between light and dark, and depicting humanism in Greek/Roman styles. The document lists and shows images of famous Renaissance artists like Michelangelo, Donatello, Da Vinci, and Raphael and some of their iconic works. Students are assigned a task analyzing Renaissance paintings or creating original art in the Renaissance style.
This document discusses features learned in Toy Task 3, including adding hyperlinks, custom animations, and slide shows. It covers applying slide layouts, inserting video and objects, adding simple animations and motion, and using word art. The goal is to replicate the information in this PPT document.
The document discusses work-life balance and its importance. It defines work-life balance as the perfect integration between work and life without interference. Poor work-life balance can lead to stress, physical problems, relational problems, decreased performance, and disturbed families. Achieving work-life balance requires planning work, providing flexibility, effective communication, organizational culture, stress management, and time management. Both organizations and employees must work together to develop strategies to help attain work-life balance.
MAGNE Consulting is headquartered in Kolkata and provides business transformation and process excellence advisory services to small and medium retail businesses. It helps clients align their people, processes, and technology using the IDAIM model to improve agility. Services include workshops, website design, digital marketing, creating standard operating procedures, audits, customer programs, and IT project management. MAGNE has successfully implemented transformations for various clients.
UniProt is a comprehensive, freely accessible database that is a central repository for protein data. It is produced through collaboration between the European Bioinformatics Institute, Swiss Institute of Bioinformatics, and Protein Information Resource. UniProt contains protein sequences, functional information, evolutionary data, and details about biological processes, post-translational modifications, interactions, and subcellular locations to characterize proteins.
UniProt is a comprehensive, freely accessible database that is a central repository for protein data. It is produced through collaboration between the European Bioinformatics Institute, Swiss Institute of Bioinformatics, and Protein Information Resource. UniProt contains protein sequences, functional information, evolutionary data, and details about biological processes, post-translational modifications, interactions, and subcellular locations to characterize proteins.
We all must do whatever is in our hands to prevent all kinds of cancer, which is the cause of millions of deaths every year. Work on your health-related presentations with the help of these editable Google Slides and PowerPoint templates.
Designing a community resource - Sandra OrchardEMBL-ABR
The document discusses designing a new community resource called the Complex Portal to describe protein complexes. It emphasizes conducting user studies, using community standards to enable data sharing and tool interoperability, and obtaining community input to ensure the resource meets researcher needs. Standards like PSI-MI and controlled vocabularies allow the resource to integrate data from other sources and enable sophisticated searches. Outreach is important to establish the resource as the primary reference.
Bioinformatics is the application of Information technology to store, organize and analyze the vast amount of biological data which is available in the form of sequences and structures of proteins and nucleic acids. The biological information of nucleic acids is available as sequences while the data of proteins is available as sequences and structures.
A biological database is a collection of data that is organized so that its contents can easily be accessed, managed, and updated. The activity of preparing a database can be divided in to:
Collection of data in a form which can be easily accessed
Making it available to a multi-user system (always available for the user)
An integrated publicly accessible bioinformatics resource to support genomic/proteomic research and scientific discovery.
Established in 1984, by the National Biomedical Research Foundation (NBRF) Georgetown University Medial Center, Washington D.C., USA.
It is the source of annotated protein databases and analysis tools for the researchers.
Serve as primary resource for the exploration of protein information.
Accessible by text search for entry and list retrieval, and also BLAST search and peptide match.
The National Center for Biomedical Ontology (NCBO) provides several software tools to enable semantically aware applications. These include BioPortal, an online library of biomedical ontologies, Ontology Widgets which allow integration of ontologies into websites, and the Annotator, a web service that semantically tags text with ontology terms. The NCBO also plans to develop a comprehensive index of online biomedical resources.
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.
This document summarizes various proteomics resources available at the EBI and ExPASy. It describes databases such as UniProt, IntAct, Reactome, and PRIDE that provide protein sequence and functional information, molecular interaction data, pathways information, and proteomics identifications respectively. It also outlines tools available at ExPASy including Hits, Prosite, SWISS-MODEL, SwissDock, and neXtProt which allow investigation of protein domains, motifs, homology modeling, protein-ligand docking, and human protein information. Additionally, it mentions STRING and VenomZone for protein-protein interaction and venom data, and various other tools for predictions, analyses, and working with proteomics data.
This document provides an overview of the Universal Protein Resource (UniProt) database. It discusses that UniProt is a comprehensive resource for protein sequence and functional data. Most protein sequences in UniProt come from gene predictions or experimental evidence. The document outlines how to search and explore UniProt entries, including how annotation scores are determined and what different evidence levels indicate. It provides guided examples of using UniProt to find protein function, link a disease to a protein and variant, and download a proteome set.
This presentation gives you a detailed information about the swiss prot database that comes under UniProtKB. It also covers TrEMBL: a computer annotated supplement to Swiss-Prot.
Protein databases contain information on protein sequences, structures, and functions. The major protein databases are:
- Protein Data Bank (PDB) which contains 3D protein structures determined via X-ray crystallography or NMR.
- Swiss-Prot which contains manually annotated protein sequences and functions.
- TrEMBL which supplements Swiss-Prot with automatically annotated translations of DNA sequences.
Protein databases are important for comparing proteins, understanding relationships between proteins, and aiding the study of new proteins. Searching databases is often the first step in protein research.
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.
Protein Sequence, Structure, and Functional Databases: UniProtKB, Swiss-Prot, TrEMBL, PIR, MIPS, PROSITE, PRINTS, BLOCKS, Pfam, NDRB, OWL, PDB, SCOP, CATH, NDB, PQS, SYSTERS, and Motif. Presented at UGC Sponsored National Workshop on Bioinformatics and Sequence Analysis conducted by Nesamony Memorial Christian College, Marthandam on 9th and 10th October, 2017 by Prof. T. Ashok Kumar
Ontology-based Tools to Enhance the Curation WorkflowTrish Whetzel
This document discusses tools from the National Center for Biomedical Ontology (NCBO) that can enhance the data curation workflow. It describes Ontology Widgets and web services that allow consistent annotation of data by reusing terms from ontologies. It also describes BioPortal Notes for collecting structured feedback to enrich ontologies, and the NCBO Annotator web service for annotating textual metadata with ontology terms. These tools address challenges of curating large amounts of data by facilitating data submission, ontology evolution, and metadata annotation.
This is the last presentation of the BITS training on 'Comparative genomics'.
It reviews tthe Contra tool for detecting common transcription factor binding sites in sequences.
Thanks to Stefan Broos of the DMBR department of VIB
This document introduces several proteomics data standards developed by the Proteomics Standards Initiative (PSI), including mzML for mass spectrometry data, mzIdentML for peptide and protein identifications, mzQuantML for quantification data, and mzTab for final identification and quantification results. It describes how these standards address the need for data standardization in proteomics as the field has evolved. It also discusses how these standards have been implemented in proteomics databases, software tools, and data repositories like ProteomeXchange to facilitate data sharing and analysis.
This is a powerpoint of automation in clinical chemistry. This comprises the definition of automation, steps of the analytical process, and detail about the continuous flow analyzer.Thus, this will be helpful for the students of medical laboratory, biochemistry students and teachers.
This document discusses mass spectrometry informatics formats developed by the Proteomics Standards Initiative. It describes standard formats such as mzIdentML, mzQuantML, and mzTab that have been created for proteomics data as well as ongoing work to extend mzTab to support metabolomics and glycomics data. It also provides information on the current status and adoption of these standards by the proteomics community.
Event: Plant and Animal Genomes conference 2012
Speaker: Michel Schneider
The UniProt Knowledgebase consists of two sections, UniProtKB/Swiss-Prot, which contains manually-annotated protein sequence enriched with functional information added by expert human curators, and UniProtKB/TrEMBL, which contains unreviewed records that are enhanced by information provided by automated rule-based annotation systems. The majority of UniProtKB records are based on automatic translation of coding sequences (CDS) provided by submitters at the time of initial deposition to the nucleotide sequence databases. In order to provide the complete proteome of Arabidopsis thaliana, a complementary curation pipeline for import of protein sequences from TAIR has been developed. As the complete genome reannotation proposed in the TAIR10 release contains most of the sequences already in UniProtKB, these existing sequences have to be reconciled with those imported. Around 7% of them have a different gene model and should be checked manually. Based on these comparisons, we improved over 200 of our predicted proteins. In exchange, we provide TAIR with the gene model corrections that we introduce on the bases of our trans-species family annotation. This approach allows identification of data that can be seamlessly transferred from one site to the other and the development of common annotations. With the significant increase in the number of complete genomes sequenced (1001 Arabidopsis cultivars are currently under way!), organization of this data in a convenient way is critical. UniProt have selected a set of “reference proteomes”, including A. thaliana cv. Columbia, which provide broad coverage of the tree of life and constitute a representative cross-section of the taxonomic diversity to be found within UniProtKB.
Event: Plant and Animal Genomes conference 2012
Speaker: Rachael Huntley
The Gene Ontology (GO) is a well-established, structured vocabulary used in the functional annotation of gene products. GO terms are used to replace the multiple nomenclatures used by scientific databases that can hamper data integration. Currently, GO consists of more than 35,000 terms describing the molecular function, biological process and subcellular location of a gene product in a generic cell. The UniProt-Gene Ontology Annotation (UniProt-GOA) database1 provides high-quality manual and electronic GO annotations to proteins within UniProt. By annotating well-studied proteins with GO terms and transferring this knowledge to less well-studied and novel proteins that are highly similar, we offer a valuable contribution to the understanding of all proteomes. UniProt-GOA provides annotated entries for over 387,000 species and is the largest and most comprehensive open-source contributor of annotations to the GO Consortium annotation effort. Annotation files for various proteomes are released each month, including human, mouse, rat, zebrafish, cow, chicken, dog, pig, Arabidopsis and Dictyostelium, as well as a file for the multiple species within UniProt. The UniProt-GOA dataset can be queried through our user-friendly QuickGO browser2 or downloaded in a parsable format via the EBI3 and GO Consortium FTP4 sites. The UniProt-GOA dataset has increasingly been integrated into tools that aid in the analysis of large datasets resulting from high-throughput experiments thus assisting researchers in biological interpretation of their results. The annotations produced by UniProt-GOA are additionally cross-referenced in databases such as Ensembl and NCBI Entrez Gene.
1 http://www.ebi.ac.uk/GOA
2 http://www.ebi.ac.uk/QuickGO
3 ftp://ftp.ebi.ac.uk/pub/databases/GO/goa
4 ftp://ftp.geneontology.org/pub/go/gene-associations
Event: Plant and Animal Genomes conference 2012
Speaker: Sandra Orchard
InterPro is an open-source protein resource used for the automatic annotation of proteins, and is scalable to the analysis of entire new genomes through the use of a downloadable version of InterProScan, which can be incorporated into an existing local pipeline. InterPro integrates protein signatures from 11 major signature databases (CATH-Gene3D, HAMAP, PANTHER, Pfam, PIRSF, PRINTS, ProDom, PROSITE, SMART, SUPERFAMILY, and TIGRFAMs) into a single resource, taking advantage of the different areas of specialization of each to produce a resource that provides protein classification on multiple levels: protein families, structural superfamilies and functionally close subfamilies, as well as functional domains, repeats and important sites. The InterPro website has been improved, following extensive community consultation and a new version of InterProScan promises improved speed, ease of implementation as well as additional functionalities.
Event: Plant and Animal Genomes Conference 2012.
Speaker: Bert Overduin
The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) provides a comprehensive record of the world's nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. Major components of ENA include the Sequence Read Archive (SRA) for next generation data and EMBL-Bank for assembled and annotated sequences. ENA works closely together with NCBI and DDBJ as partners in the International Nucleotide Sequence Database Collaboration (INSDC). Data arrive at ENA from a variety of sources. These include submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centres and routine and comprehensive exchange with our INSDC partners. Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and provides a portfolio of interactive and programmatic submission services to ensure the smoothest flow possible of data into the public domain. ENA data can be searched using rapid sequence similarity and text search services provided both within web-based tools and under programmatic interfaces. Data can be retrieved in a variety of appropriate widely adopted formats through a web browser and extensive REST services. This presentation will consist of an introduction to ENA, followed by a short demonstration of the various ways data can be browsed and retrieved.
Genome resources at EMBL-EBI: Ensembl and Ensembl GenomesEBI
Event: Plant and Animal Genomes Conference
Speaker: Bert Overduin
The Ensembl project (http://www.ensembl.org) seeks to enable genomic science by providing high quality, integrated annotation on chordate and selected eukaryotic genomes. All supported species include comprehensive, evidence-based gene annotations and a selected set of genomes includes additional data focused on variation, comparative, evolutionary, functional and regulatory annotation. As of Ensembl release 65 (December 2011), 56 species are fully supported. Ensembl data are accessible through an interactive web site, flat files, the data mining tool BioMart, direct database querying and a set of Perl APIs. Moreover, Ensembl is not just a data visualisation tool, but a suite of programs for data production (e.g. gene calling and comparative genomics) that can be deployed individually according to the needs of an individual community. Ensembl Genomes (http://www.ensemblgenomes.org) consists of five sub-portals (for bacteria, protists, fungi, plants and invertebrate metazoa) designed to complement the genomes available in Ensembl. It currently contains data for over 300 species. Many of the databases that support Ensembl Genomes have been built by, or in close collaboration with, groups that maintain specialist data resources for individual species, and we are actively seeking to extend the range of these collaborations. Together Ensembl and Ensembl Genomes offer a single unified interface across the taxonomic space. This presentation will consist of a short introduction to Ensembl and Ensembl Genomes followed by a demonstration of the respective websites and the BioMart data retrieval tool. Special attention will be given to recently developed functionality like the Variant Effect Predictor, which predicts the consequences of substitutions, insertions and deletions on transcripts and protein sequences, and the possibility to visualize your own data by attaching BAM and VCF files (for example).
Event: Plant and Animal Genomes conference
Speaker: Jane Loveland (Wellcome Trust Sanger Institute
The Human and Vertebrate Analysis and Annotation (HAVANA) team at the Wellcome Trust Sanger Institute (WTSI) undertakes manual annotation of finished vertebrate genomic sequence. This annotation is available from the Vertebrate Genome Annotation database (VEGA) (http://vega.sanger.ac.uk) and is in progress for whole genomes (human, mouse and zebrafish) and specific regions of interest, such as pig (SLA and LRC), dog (DLA), wallaby (MHC), gorilla (MHC and LRC). Manual annotation of genomic data is extremely valuable to produce an accurate reference gene set but is expensive compared with automatic methods and so has been limited to model organisms. Annotation tools that have been developed at the Wellcome Trust Sanger Institute are being used to fill that gap, as they can be used remotely and so open up viable community annotation collaborations. We introduce the “Blessed” annotator and “Gatekeeper” approach to Community Annotation using the Otterlace/ZMap genome annotation tool. We also describe the strategies adopted for annotation consistency, quality control and viewing of the annotation. We are currently involved in the annotation of immune response genes in pig and have annotated over 1700 genes in a community annotation effort, together with the sequencing and annotation of pig chromosomes X and Y at WTSI that will be displayed on the VEGA website. Presented on behalf of the HAVANA team, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambs UK.
Event: Plant and Animal Genomes Conference 2012
Speaker: Cath Brooksbank
Train online (www.ebi.ac.uk/training/online/) is a free, web-based learning resource for life scientists. Train online helps you make the most of the huge amount of biological data that EMBL-EBI makes publicly available for the research community. Using a combination of tutorials, guided examples, exercises and quizzes, Train online guides you towards becoming a confident user of open-access data resources. This training portal is there for you to learn in your own time and at your own pace, anywhere in the world. You do not need previous experience in bioinformatics to benefit from our courses.
This presentation will provide a short introduction to the courses currently available in Train online, which will include a demonstration of the resource. After the demonstration, the speaker will welcome questions about Train online and any suggestions that you may have for future courses.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
2. Talk outline
• Introduction to UniProt
• UniProtKB annotation and propagation
• Data increase and the need for Automatic Annotation
• Automatic annotation systems in UniProtKB
• UniRule Automatic Annotation System
• Complete Proteomes in UniProtKB
30 January 2015
2
3. Talk outline
• Introduction to UniProt
• UniProtKB annotation and propagation
• Data increase and the need for Automatic Annotation
• Automatic annotation systems in UniProtKB
• UniRule Automatic Annotation System
• Complete proteomes in UniProtKB
30 January 2015
3
4. 30 January 2015
4
UniProt Consortium
• Formed in 2002
• Previously known as “Swiss-Prot” since 1986
• UniProt group at the EBI is led by Claire Odonovan and Maria
Jesus Martin, part of the PANDA proteins group led by Rolf
Apweiler
• UniProt group at PIR, Georgetown University is led by Cathy Wu
• UniProt group at SIB (Geneva/Lausanne) is led by Ioannis
Xenarios and Lydie Bougeleret (heirs to Amos Bairoch, left 2009)
• UniProtKB is UniProt KnowledgeBase, and includes TrEMBL and
Swiss-Prot entries
6. UniProt databases
30 January 2015
6
ENA/GenBank/DDBJ, Ensembl, VEGA, RefSeq, other sequence resources
UniSave
- Providing entry
version history
UniSave
- Providing entry
version history
7. Talk outline
• Introduction to UniProt
• UniProtKB annotation and propagation
• Data increase and the need for Automatic Annotation
• Automatic annotation systems in UniProtKB
• UniRule Automatic Annotation System
• Complete Proteomes in UniProtKB
30 January 2015
7
12. 30 January 2015
12
Propagation of annotation in UniProtKB
Annotation Propagated
RecName Yes
AltName Yes
Function Yes
Catalytic activity Yes
Pathway Yes
Subunit Yes
Subcellular location Yes
Disease No
Disruption phenotype No
Polymorphism No
Alternative products No
Generalannotation_______
Featureannotation_______
Annotation Propagated
KW Yes
GO Yes
Regions of interest Yes
Active site Yes
Ligand-binding Yes
Processing Yes
PTMs Yes
Ambiguities No
Conflicts No
Natural variants No
Isoforms No
13. Talk outline
• Introduction to UniProt
• UniProtKB annotation and propagation
• Data increase and the need for Automatic Annotation
• Automatic annotation systems in UniProtKB
• UniRule Automatic Annotation System
• Complete Proteomes in UniProtKB
30 January 2015
13
15. 30 January 2015
15
Benefits of Automatic Annotation
• Added value for TrEMBL in the face of rapid data growth
• many species/proteins without published experimental data
• Support for manual curation
• making manual curation of TrEMBL entries for which there is
published data easier
• Correction of misleading annotation in data received from
sequencing centres
• Highlighting of patterns
• knowledge that can be/needs to be propagated across the
databases
• inconsistent annotation e.g. of a protein family
16. Talk outline
• Introduction to UniProt
• UniProtKB annotation and propagation
• Data increase and the need for Automatic Annotation
• Automatic annotation systems in UniProtKB
• UniRule Automatic Annotation System
• Complete Proteomes in UniProtKB
30 January 2015
16
17. 30 January 2015
17
Automatic Annotation in UniProtKB/TrEMBL
We have implemented Automatic Annotation systems based
on annotation rules
•Rules are linked to specific signatures - InterPro
•Annotation rules have
• annotations
• conditions
•Rules are tested and validated against UniProtKB/Swiss-
Prot
•Rules and annotations are updated each UniProt release
18. Automatic Annotation Systems in UniProtKB
System
Rule
creation
Trigger Annotations Scope
SAAS automatic
taxonomy
InterPro
comments, KW all taxa
UniRule
(Rulebase/HAMAP/
PIRNR/PIRSR)
manual
taxonomy
InterPro*
proteome
property
sequence
length
protein names,
comments,
features, KW,
GO terms
all taxa
30 January 2015
18
* Flexibility to create custom signatures and submitted to InterPro as required
19. Principle of an Annotation Rule Creation
30 January 2015
19
annotated Swiss-Prot entries rule TrEMBL entries
extract common
annotation
propagate
taxonomic nodes
Interpro entries and member signatures
proteome properties
sequence length
TrEMBL entries remain in TrEMBL, but offer more (predicted) annotation
20. 30 January 2015
20
SAAS – Statistically Automatic Annotation System
• Automatically generated annotation rule system to
supplement the labour intensive UniRule system
• Employs a C4.5 decision-tree algorithm to find the most
concise rule
21. Talk outline
• Introduction to UniProt
• UniProtKB annotation and propagation
• Data increase and the need for Automatic Annotation
• Automatic annotation systems in UniProtKB
• UniRule Automatic Annotation System
• Complete Proteomes in UniProtKB
30 January 2015
21
22. 30 January 2015
22
UniRule Automatic Annotation System
• Manually created/curated rules of varying complexity:
annotation varies from simple Keyword attribution to
complete annotation
• Sources for rule creation
• automatically generated SAAS rules as input
• literature based curation of characterised families – as a
potential source for creating new signatures for a specific
functional group
• also …
23. UniRule - conditions used to created a rule
Conditions (can be positive or negative)
•Taxonomy
•InterPro entries and member signatures
•Subcellular location e.g. organelles
•Proteome properties e.g. photosynthetic
•Sequence length
30 January 2015
23
24. UniRule – UniProtKB annotations defined in a rule
Annotations
•Description lines
• Protein names
• EC numbers
•Gene names
•General annotation (comments)
•UniProtKB Keywords
•GO terms
30 January 2015
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29. Talk outline
• Introduction to UniProt
• UniProtKB annotation and propagation
• Data increase and the need for Automatic Annotation
• Automatic annotation systems in UniProtKB
• UniRule Automatic Annotation System
• Complete Proteomes in UniProtKB
30 January 2015
29
30. How does UniProt define a Complete
proteome?
• A complete proteome consists of the set of proteins
thought to be expressed by an organism whose genome
has been completely sequenced.
30 January 2015
30
31. Status of complete proteomes in UniProt
• Longstanding project, 2902 proteomes that are spread over the
entire taxonomic range
• Archaea
• Bacteria
• Eukaryota
• Viruses
• Capture of “Complete proteome” data is a mixture of automatic and
manual procedures
• Aim is to provide a set of UniProtKB entries that define the proteome
30 January 2015
31
32. Human complete proteome
• First draft of the complete human proteome available in
UniProtKB/Swiss-Prot in September 2008
• The first mammalian proteome to be annotated
• Representing approximately 20,000 putative protein-coding
genes each represented by one canonical sequence
30 January 2015
32
33. Other complete proteomes
Human not the only organism to have its proteome annotated
•Sus scrofa (Pig) – 19,576 entries
•Gallus gallus (Chicken) – 21,622 entries
•Mus musculus (Mouse) – 46,656 entries
•Arabidopsis thaliana (Mouse-ear cress) - 32,521 entries
30 January 2015
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34. Challenges of proteome data
• How to define a complete genome, what is complete? Does it have a
complete set of gene model annotations?
• Track any changes in the genome annotations and the impact on
UniProt
• Gather all proteomes available, develop import pipelines to improve
species coverage, current sources include:
• INSDC species
• Ensembl species
• UniProtKB also define a subset of the Complete proteomes as being
'Reference proteomes'.
• Complete proteome of a representative, well-studied model organism or
an organism of interest for biomedical research.
30 January 2015
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37. Closing remarks
• Manual annotation cannot keep pace with current or future
rates of growth of UniProtKB so there is a need for automatic
annotation
• UniProtKB currently uses two automatic annotation systems
referred to as SAAS and UniRule
• Automatic annotation of TrEMBL is refreshed and validated
using UniProtKB/Swiss-Prot as a reference, each UniProtKB
release
30 January 2015
37
38. Closing remarks
• UniRule – manually annotated rules
• annotation varies from simple keywords to full annotation
• starting from SAAS rules, InterPro signatures, literature-based
curation of protein families
• possibility to create custom signatures for InterPro
• Evidence attribution - users to determine the composition
of the rule behind predicted annotation
30 January 2015
38
39. Closing remarks
• Requirements for completed proteomes
• Completely sequenced genome
• Good gene prediction models
• Good quality transcriptome/proteome data
• Proteins are mapped to genome
30/01/15
39
40. Acknowledgements
• UniProt group at the EBI is led by Claire Odonovan and Maria
Jesus Martin, part of the PANDA proteins group led by Rolf
Apweiler
• UniProt group at PIR, Georgetown University is led by Cathy
Wu
• UniProt group at SIB (Geneva/Lausanne) is led by Ioannis
Xenarios and Lydie Bougeleret (heirs to Amos Bairoch, left
2009)
• Thanks also to all curators, developers and support staff at
all three sites
30 January 2015
40
41. Funding
• National Institutes of Health (NIH)
• European Commission (EC)'s SLING
• Swiss Federal Government through the Federal Office of
Education and Science
• GEN2PHEN
• MICROME
• National Science Foundation (NSF)
30 January 2015
41
Editor's Notes
Good morning. My name is Wei Mun Chan and I am a UniProt curator working at the European Bioniformatics Institute, in Hinxton, UK.
In the following session I will talk about Automatic Annotation as it is used in UniProtKB, focusing on UniRAule, and I will subsequently talk about Complete Proteomes in UniProtKB.
Firstly, I will talk about the background to UniProt.
I’ll then go on to describe UniProtKB annotation and propagation of this annotation.
Moving on, I will talk about the growth of data in UniProtKB and the need for Automatic Annotation to cope with this data.
I’ll then describe the Automatic Annotation Systems we use in UniProtKB.
And to end, I will describe UniProtKB Complete Proteomes.
The UniProt Consortium was formed in 2002 – together to provide the Universal Protein Resource UniProt.
This is a screenshot of the UniProt Resource, which is available at the URL www.uniprot.org.
This is the entry point to the various resources offered by UniProt.
The mission of UniProt is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequence and functional information.
UniProt provides several databases including:
UniSave – which contains the entry version history for UniProtKB entries.
UniRef – sequence cluster database.
UniMES – stores metagenomic and environmental sequences.
UniParc – Sequence archive
The centre piece of UniProt’s activities is the UniProt KnowledgeBase UniProtKB, which contains the Manually reviewed UniProtKB/Swiss-Prot entries and Unreviewed TrEMBL entries.
Unreviewed UniProtKB/TrEMBL entries are manually reviewed by experts and upon integration/become reviewed UniProtKB/Swiss-Prot entries. Automatic Annotation procedures then feed back into the UniProtKB/TrEMBL database.
Now to give you a brief overview of the information annotated in a UniProtKB entry.
Take the human protein Ky-nu-renin-ase as an example. This is a screenshot taken of the top section of the protein entry as it is represented in the UniProtKB database.
As you can see the protein has been manually annotated, Reviewed entry and therefore resides in the UniProtKB/Swiss-Prot database.
Within this entry, we provide a Recommended name, Alternative name, Gene Symbol, Organism and Taxonomy.
In addition, within the entry we also provide further information that can be attributed to the protein in General annotation comments section. Here we collate valuable protein characterisation information.
Annotation in UniProtKB also includes the annotation of Ontologies.
And this includes the annotation of UniProtKB-specific Keywords and also the complimentary Gene Ontology terms.
We also provide sequence feature annotation – where we describe for example how the molecule is processed, regions, sites within the sequence. Also amino acid modifications and natural sequence variations.
This slide captures the graphical representation of sequence features in UniProtKB.
As part of our manual annotation efforts we also propagate annotation from proteins where the annotation has been demonstrated experimentally.
We restrict the propagation between closely related species, or if appropriate also to distantly related species where the proteins are well-conserved.
This table lists some of the categories of annotations that we do or do not propagate between UniProtKB entries.
This graph illustrates the disparity between the growth in the number of:
Manually reviewed UniProtKB/Swiss-Prot entries represented by the red line.
Unreviewed automatically generated UniProtKB/TrEMBL entries represented by the green line.
Thus, our manual curation efforts is being outpaced by the growth in the unreviewed data. There is therefore a need to enrich these unreviewed UniProt/TrEMBL entries we annotate.
How. Through the use of Automatic Annotation.
What are the benefits of Automatic Annotation?
Firstly, to enrich unreviewed entries in TrEMBL in the face of rapid data growth. There are many species/proteins without published experimental data.
Secondly, to support our manual curation efforts. Making manual curation of unreviewed TrEMBL entries for which there is published data easier.
Thirdly, to correct misleading annotation in data received from sequencing centres.
Fourthly, to help highlight patterns. Recognise knowledge that CAN or NEEDs to be propagated across the databases. Also to help spot, inconsistent annotation e.g. of a protein family.
How is Automatic Annotation in UniProtKB/TrEMBL accomplished?
We have implemented Automatic Annotation systems based on Annotation rules.
Rules are linked to specific signatures – InterPro.
Rules are associated with – annotations and conditions.
Rules are tested and validated against UniProtKB/Swiss-Prot.
Rules and annotations are updated each UniProt release.
UniProtKB currently employs two automatic annotation systems – referred to as SAAS and UniRule.
Recognises common annotation belonging to a closely related family within UniProtKB/Swiss-Prot
Transfer of common annotation to related family members in UniProtKB/TrEMBL
The manually curated UniRules annotation system – incorporates the HAMAP, RuleBase, PIRNR/SR systems.
This slide shows a simplified overview of how Annotation rules work in UniProtKB.
Rules are built by a combination of specific conditions (grey box) and associated with common annotation from UniProtKB/Swiss-Prot entries.
The rules identify/extract common annotation present in UniProtKB entries (represented by the highlighted red grids) and then propagate these annotations to unreviewed TrEMBL entries.
Thus, the annotationally enriched TrEMBL entries remain in TrEMBL.
The first of the Automatic Annotation Systems used in UniProtKB is:
Statistically Automatic Annotation System abbreviated SAAS.
Supplements the labour intensive manual curation of rules in the UniRule system.
C4.5 algorithm uses entropy gain to find most concise rule.
Manually created/curated rules of varying complexity. Simple UniProtKB Keyword to complete annotation.
Sources for rule creation – roughly categorised into four categories:
1) Automatically generated SAAS rules as input.
2) Literature-based curation of characterised families – as a potential source for creating new signatures for specific functional group
And also:
3. Conditions.
And 4. Annotations.
This is a screenshot to show how links to UniRule rules is represented in a UniProtKB entry.
We can see that the rule of interest is UniRule/RuleBase RU003777.
Information that has been propagated to this UniProtKB/TrEMBL entry by this rule is followed by the RuleBase evidence tag.
The same evidence tag also appears associated with General Annotation and Ontologies.
Clicking one of these tags/links allows us to view the predicted annotations and the rule itself.
On a left we see the predicted annotations. And on the right we see the conditions used to build the rule (conditions can be positive or negative).
On a left we see the predicted annotations. And on the right we see the conditions used to build the rule (conditions can be positive or negative).
So what are some of the challenges UniProt faces when dealing with Complete Proteome data?
How do we define a complete genome, and decide what is complete?
For example - does it have a complete set of gene model annotations?
There is a need to track changes in genome annotations and how these changes impact on UniProt.
Gather all proteomes available,