In science, data visualization serves two primary purposes. The first is to explore data sets interactively and the second is to communicate discoveries. However, the requirements for visualizations employed in these activities are very different. Therefore, the software tools used for these purposes are typically disconnected, creating significant challenges for reproducibility and effective communication of discoveries in data-driven biomedical science. In this presentation, I will address how a new approach to creating data visualization tools can connect data analysts and other stakeholders inside and outside the scientific community. I will introduce and demonstrate the "Vistories" approach that was motivated by these question.
Presented at the 5th Cancer Research UK Big Data Analytics Conference on Data Visualization.
Making the most of phenotypes in ontology-based biomedical knowledge discoveryMichel Dumontier
A phenotype is an observable characteristic of an individually and typically pertains to its morphology, function, and behavior. Phenotypes, whether observed at the bench or the bedside, are increasingly being used to gain insight into the diagnosis, mechanism, and treatment of disease. A key aspect of these approaches involve comparing phenotypes that are defined in multiple terminologies that often cater to altogether different organisms, such as mice and humans. In this seminar, I will discuss computational approaches for harmonizing and utilizing phenotypes for translational research. We will examine case studies which involve the computation of semantic similarity including the use of phenotypes to inform clinical diagnosis of rare diseases, to identify human drug targets using mice knock-out models, and to explore phenotype-based approaches for drug repositioning .
The Monarch Initiative: From Model Organism to Precision Medicinemhaendel
NIH BD2K all-hands meeting poster November 12, 2015.
Attempts at correlating phenotypic aspects of disease with causal genetic influences are often confounded by the challenges of interpreting diverse data distributed across numerous resources. New approaches to data modeling, integration, tooling, and community practices are needed to make efficient use of these data. The Monarch Initiative is an international consortium working on the development of shared data, tools, and standards to enable direct translation of integrated genotype, phenotype, and environmental data from human and model organisms to enhance our understanding of human disease. We utilize sophisticated semantic mapping techniques across a diverse set of standardized ontologies to deeply integrate data across species, sources, and modalities. Using phenotype similarity matching algorithms across these data enables disorder prediction, variant prioritization, and patient matching against known diseases and model organisms. These similarity algorithms form the core of several innovative tools. The Exomiser, which enables exome variant prioritization by combining pathogenicity, frequency, inheritance, protein interaction, and cross-species phenotype data. Our Phenotype Sufficiency tool provides clinicians the ability to compare patient phenotypic profiles using the Human Phenotype Ontology to determine uniqueness and specificity in support of variant prioritization. The PhenoGrid visualization widget illustrates phenotype similarity between patients, known diseases, and model organisms. Monarch develops models in collaboration with the community in support of the burgeoning genotype-phenotype disease research community. We have successfully used Exomiser to solve a number of undiagnosed patient cases in collaboration with the NIH Undiagnosed Disease Program. Ongoing development in coordination with the Global Alliance for Genetic Health (GA4GH) and other groups will catalyze the realization of our goal of a vital translational community focused on the collaborative application of integrated genotype, phenotype, and environmental data to human disease.
This presentation was provided by Alberto Pepe of Authorea, during the NISO hot topic event "Preprints." The virtual conference was held on April 21, 2021.
This presentation was provided by Leslie McIntosh of Ripeta, during the NISO hot topic event "Preprints." The virtual conference was held on April 21, 2021.
Leveraging Publicly Accessible Clinical Trails Data Sharing, Dissemination an...Vaticle
In the broader realm of the advancement of science and the betterment of the human condition, there are several purported benefits for sharing clinical trials and research data. The scientific community has just begun to embrace open-access datasets to build their knowledge base, gain insight into new discoveries, and generate novel data-driven hypotheses that were not initially formulated in the studies. With the increasing amount of clinical trial data available, comes the need to leverage a multitude of shared datasets. Your knowledge base needs to facilitate discovery across research domains.
This talk highlights the data sharing, dissemination, and repurposing of clinical and molecular studies generated by government-funded research consortia. Further, we are building a new knowledge base resource, IMMGRAKN to facilitate translational discovery from crowd-sourced clinical trials data in ImmPort (www.immport.org), an NIH-NIAID funded open-access immunology database and analysis portal. The case studies demonstrating the use of IMMGRAKN will be discussed
Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...GigaScience, BGI Hong Kong
Scott Edmunds talk at IARC, Lyon. How can we make science more trustworthy and FAIR? Principled publishing for more evidence based research. 8th July 2019
Making the most of phenotypes in ontology-based biomedical knowledge discoveryMichel Dumontier
A phenotype is an observable characteristic of an individually and typically pertains to its morphology, function, and behavior. Phenotypes, whether observed at the bench or the bedside, are increasingly being used to gain insight into the diagnosis, mechanism, and treatment of disease. A key aspect of these approaches involve comparing phenotypes that are defined in multiple terminologies that often cater to altogether different organisms, such as mice and humans. In this seminar, I will discuss computational approaches for harmonizing and utilizing phenotypes for translational research. We will examine case studies which involve the computation of semantic similarity including the use of phenotypes to inform clinical diagnosis of rare diseases, to identify human drug targets using mice knock-out models, and to explore phenotype-based approaches for drug repositioning .
The Monarch Initiative: From Model Organism to Precision Medicinemhaendel
NIH BD2K all-hands meeting poster November 12, 2015.
Attempts at correlating phenotypic aspects of disease with causal genetic influences are often confounded by the challenges of interpreting diverse data distributed across numerous resources. New approaches to data modeling, integration, tooling, and community practices are needed to make efficient use of these data. The Monarch Initiative is an international consortium working on the development of shared data, tools, and standards to enable direct translation of integrated genotype, phenotype, and environmental data from human and model organisms to enhance our understanding of human disease. We utilize sophisticated semantic mapping techniques across a diverse set of standardized ontologies to deeply integrate data across species, sources, and modalities. Using phenotype similarity matching algorithms across these data enables disorder prediction, variant prioritization, and patient matching against known diseases and model organisms. These similarity algorithms form the core of several innovative tools. The Exomiser, which enables exome variant prioritization by combining pathogenicity, frequency, inheritance, protein interaction, and cross-species phenotype data. Our Phenotype Sufficiency tool provides clinicians the ability to compare patient phenotypic profiles using the Human Phenotype Ontology to determine uniqueness and specificity in support of variant prioritization. The PhenoGrid visualization widget illustrates phenotype similarity between patients, known diseases, and model organisms. Monarch develops models in collaboration with the community in support of the burgeoning genotype-phenotype disease research community. We have successfully used Exomiser to solve a number of undiagnosed patient cases in collaboration with the NIH Undiagnosed Disease Program. Ongoing development in coordination with the Global Alliance for Genetic Health (GA4GH) and other groups will catalyze the realization of our goal of a vital translational community focused on the collaborative application of integrated genotype, phenotype, and environmental data to human disease.
This presentation was provided by Alberto Pepe of Authorea, during the NISO hot topic event "Preprints." The virtual conference was held on April 21, 2021.
This presentation was provided by Leslie McIntosh of Ripeta, during the NISO hot topic event "Preprints." The virtual conference was held on April 21, 2021.
Leveraging Publicly Accessible Clinical Trails Data Sharing, Dissemination an...Vaticle
In the broader realm of the advancement of science and the betterment of the human condition, there are several purported benefits for sharing clinical trials and research data. The scientific community has just begun to embrace open-access datasets to build their knowledge base, gain insight into new discoveries, and generate novel data-driven hypotheses that were not initially formulated in the studies. With the increasing amount of clinical trial data available, comes the need to leverage a multitude of shared datasets. Your knowledge base needs to facilitate discovery across research domains.
This talk highlights the data sharing, dissemination, and repurposing of clinical and molecular studies generated by government-funded research consortia. Further, we are building a new knowledge base resource, IMMGRAKN to facilitate translational discovery from crowd-sourced clinical trials data in ImmPort (www.immport.org), an NIH-NIAID funded open-access immunology database and analysis portal. The case studies demonstrating the use of IMMGRAKN will be discussed
Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...GigaScience, BGI Hong Kong
Scott Edmunds talk at IARC, Lyon. How can we make science more trustworthy and FAIR? Principled publishing for more evidence based research. 8th July 2019
BioVariance - Pediatric Pharmacogenomics in Drug DiscoveryJosef Scheiber
This slideset gives an overview of pharmacogenomic and pediatric dosing knowledge and various influence factors. Finally it shows an example on how to use this kind of Data within predictive approaches.
No Boundary Thinking in Bioinformatics Workshop KeynoteCasey Greene
"The bounty of the commons"
In this talk, we explore how public data can become more valuable with reuse. This reuse helps us get to the bottom of cases where we are certain and wrong and helps us ask better questions.
Linking assertions to evidence with the MicroPublications ontology WG evidenc...jodischneider
How can we link assertions to evidence in the scientific literature?
Discussion about the MicroPublications ontology (http://purl.org/mp/ & see http://arxiv.org/abs/1305.3506 )
Presented to the WG Evidence Panel of the Addressing PDDI Evidence Gaps project https://sites.google.com/site/ddikrandir/home/wg-evidence-panel
Data analytics to support exposome research course slidesChirag Patel
We present new publicly available tools to bootstrap your own data-driven investigations to correlate the environment with phenotype. Course materials here: http://www.chiragjpgroup.org/exposome-analytics-course/
BioVariance - Pediatric Pharmacogenomics in Drug DiscoveryJosef Scheiber
This slideset gives an overview of pharmacogenomic and pediatric dosing knowledge and various influence factors. Finally it shows an example on how to use this kind of Data within predictive approaches.
No Boundary Thinking in Bioinformatics Workshop KeynoteCasey Greene
"The bounty of the commons"
In this talk, we explore how public data can become more valuable with reuse. This reuse helps us get to the bottom of cases where we are certain and wrong and helps us ask better questions.
Linking assertions to evidence with the MicroPublications ontology WG evidenc...jodischneider
How can we link assertions to evidence in the scientific literature?
Discussion about the MicroPublications ontology (http://purl.org/mp/ & see http://arxiv.org/abs/1305.3506 )
Presented to the WG Evidence Panel of the Addressing PDDI Evidence Gaps project https://sites.google.com/site/ddikrandir/home/wg-evidence-panel
Data analytics to support exposome research course slidesChirag Patel
We present new publicly available tools to bootstrap your own data-driven investigations to correlate the environment with phenotype. Course materials here: http://www.chiragjpgroup.org/exposome-analytics-course/
A Unified Approach to Exploration, Authoring, and Communication with Reproduc...Nils Gehlenborg
Visualization plays two essential roles in data-driven scientific discovery. First, visualization is a key tool for data exploration and hypothesis generation. Second, visualization facilitates communication of insights and findings. In a typical analysis scenario, however, visualization for exploration and visualization for communication are two separate processes. They often involve different software tools and data representations. Even though sophisticated interactive visualization tools are available to explore data sets, findings are usually shared in form of static images or functionally limited interactive visualizations. While these capture a particular state, they do not include any information about the exploration process that lead to the finding.
In this talk I will describe how by capturing the visual exploration process, visualizations can be made reproducible and sharable. My collaborators and I leverage such data about the analysis process to allow analysts to create "vistories", which are interactive and annotated figures, that communicate insights and findings.
Receiving the John Kendrew Award is a great honour for me, and I am humbled to be joining the ranks of the previous recipients. None of this would have been possible without the many people who influenced my career at EMBL and Harvard Medical School, in particular, my past and present mentors. To me, the John Kendrew Award is not only a recognition of my achievements. I also consider it an acknowledgment of the importance of my field—visualisation of biomedical data—which was in its infancy when I started my PhD at the EMBL-EBI in 2006.
https://www.embl.de/aboutus/alumni/news/news_2018/20180302_gehlenborg/index.html
Visual Exploration of Clinical and Genomic Data for Patient StratificationNils Gehlenborg
Talk presented at the Simons Foundation Biotech Symposium "Complex Data Visualization: Approach and Application" (12 September 2014)
http://www.simonsfoundation.org/event/complex-data-visualization-approach-and-application/
In this talk I describe how we integrated a sophisticated computational framework directly into the StratomeX visualization technique to enable rapid exploration of tens of thousands of stratifications in cancer genomics data, creating a unique and powerful tool for the identification and characterization of tumor subtypes. The tool can handle a wide range of genomic and clinical data types for cohorts with hundreds of patients. StratomeX also provides direct access to comprehensive data sets generated by The Cancer Genome Atlas Firehose analysis pipeline.
http://stratomex.caleydo.org
Interpreting data from cohort studies where clinical and molecular data across hundreds to thousands of patient samples need to be integrated, potentially spanning multiple time points, is challenging. In this presentation, I will discuss how data visualization can be used to drive or support this process, using tools that are applying the concept of “divide and conquer” to visual exploration. I will be presenting our early work on StratomeX and illustrate how this approach led to techniques such as Domino and LineUp, and will also introduce OncoThreads and Lineage, tools that we designed for visualization of cohorts with temporal and genealogical information, respectively.
From Genomics to Medicine: Advancing Healthcare at ScaleDatabricks
With the exponential growth of genomic data sets, healthcare practitioners now have the opportunity to improve human outcomes at an unprecedented pace. These outcomes are difficult to realize in the existing ecosystem of genomic tools, where biostatisticians regularly chain together command-line interfaces based on a single-node setup on premise. The Databricks Unified Analytics Platform for Genomics empowers users to perform end-to-end analysis on our massively scalable platform in the cloud: in only minutes, a data scientist can visualize an individual’s disease risk based on their raw genomic data. Built on Apache Spark, we provide click-button implementations of accepted best practice workflows, as well as low-level Spark SQL optimizations for common genomics operations.
This year's 3rd Annual TCGC: The Clinical Genome Conference, held June 10-12, 2014 in San Francisco, is a three-day event that weaves together the science of sequencing and the business of implementing genomics in the clinic. It uniquely illustrates the mutual influence of those areas and the need to therefore consider the needs, challenges and opportunities of both - from next-generation sequencing and variant interpretation to insurance reimbursement and electronic health records - throughout the entire research process.Learn more at http://www.clinicalgenomeconference.com
Using Public Access Clinical Databases to Interpret NGS VariantsGolden Helix Inc
In this webcast on February 19th, Gabe Rudy, Vice President of Product Development, will showcase publicly available databases and resources available for interpreting rare and novel mutations in the context of his own personal exome obtained through a limited 23andMe pilot in 2012.
The last couple years have seen many changes in well-established resources such as OMIM and dbSNP, while motivating new efforts such as ClinVar and PhenoDB to bring NGS interpretation to clinical grade through a global data sharing effort.
In this webcast, Gabe will cover:
The changing landscape of public annotations: Then, Now, and Soon.
Will the new human reference (GRCh38) released in December be a game changer?
Specific examples of improvements in annotation and algorithms that result in more accurate analysis of his own exome.
The utility and progress of NGS to different clinical applications in terms of public resources: carrier screening, hereditary cancer risk, pharmacogenomics, oncology care, and genetic disorder diagnosis.
Sharing of new clinical data: How both variation and phenotype level data is currently being shared and what will be the way forward to match rare and undiagnosed cases at a global scale.
In this talk, we present our work on developing large-scale text mining and machine learning tools as well as their uses in real-world applications in PubMed search, biocuration and healthcare (medical image analysis).
Morphologomics - Challenges for Surgical Pathology in the Genomic Age by Dr. ...Cirdan
This presentation introduces and discussesthe concept of ‘morphologomics’ that is omics approaches critically reimagined and reappraised from the viewpoint of classic morphology.
It was delivered by Dr. Anthony Gill at the Pathology Horizons 2017 conference in Cairns, Australia.
introduce and discuss the concept of ‘morphologomics’ that is omics approaches critically reimagined and reappraised from the viewpoint of classic morphology.
Visualization Tools for the Refinery Platform - Supporting reproducible resea...Nils Gehlenborg
The Refinery Platform (http://www.refinery-platform.org) is a web-based data visualization and analysis system for epigenomic and genomic data designed to support reproducible biomedical research. The analysis backend employs the Galaxy Workbench and connects to a data repository based on the ISA-Tab data description format. In my talk I will discuss the exploratory visualization tools that we have integrated into Refinery.
How to transform genomic big data into valuable clinical informationJoaquin Dopazo
How to transform genomic big data into valuable clinical information
The impact of genomics in translational medicine: present view
13th October 2014, Vall d’Hebron Institute of Research (VHIR), Barcelona, Spain
A systematic approach to Genotype-Phenotype correlationsfisherp
It is increasingly common to combine Microarray and Quantitative Trait Loci data to aid the search for candidate genes responsible for phenotypic variation. Workflows provide a means of systematically processing these large datasets and also represent a framework for the re-use and the explicit declaration of experimental methods. Here we highlight the issues facing the manual analysis of microarray and QTL data for the discovery of candidate genes underlying complex phenotypes. We show how automated approaches provide a systematic means to investigate genotype-phenotype correlations. This methodology was applied to a use case of resistance to African trypanosomiasis in the mouse. Pathways represented in the results identified Daxx as one of the candidate genes within the Tir1 QTL region.
Power to the People: Data Visualization in Biology and MedicineNils Gehlenborg
In this talk, I discuss how data visualization contributes to the democratization of data in biology and medicine. I emphasize the need to increase visualization literacy in order to achieve true democratization of biomedical data.
Mining Gems from the Data Visualization LiteratureNils Gehlenborg
What is the data visualization community and what can we learn from it?
What are some great examples?
What are the reasons why we don’t see more of this work in bioinformatics? The valley death ...
Talk presented at a Bayer Data Science Meetup. How can data visualization bridge between analysts and decision makers? How can we enable data-driven discovery with visualization and data-driven communication? I introduce and demonstrate the Vistories approach motivated by the reproducibility crisis in science.
HiGlass + HiPiler: Making Sense of Chromosome Interaction Data with Multi-Sca...Nils Gehlenborg
How can we visualize a 3,000,000 x 3,000,000 cell matrix and allow analysts to explore features across a wide range of different scales? We built HiGlass, a web-based visualization tool for analysis of Hi-C and other genome-wide chromosome interaction data that enables comparison of multiple contact matrices and integration of other data types. To complement this functionality, we also created HiPiler, which enables investigators to view and explore thousands of features such as loops or TADs and correlate their appearance with their genomic locations and experimental conditions. In my talk, I will discuss the design of HiGlass and HiPiler and present a range of use cases for these applications.
(Thanks to Fritz Lekschas for providing many of the slides.)
Multi-Scale Visualization Tools for Exploration of Chromosome Interaction ...Nils Gehlenborg
How do you visualize a 3 million x 3 million matrix and allow users to explore features across a wide range of different scales? We built HiGlass and HiPiler, web-based visualization tools for analysis of Hi-C and other genome-wide chromosome interaction data that enables comparison of multiple contact matrices and integration of other data types. In my talk, I will discuss several use cases and describe how we architected HiGlass and HiPiler.
Approaches for the Integration of Visual and Computational Analysis of Biomed...Nils Gehlenborg
The integration of computational and statistical approaches with visualization tools is becoming crucial as biomedical data sets are rapidly growing in size. Finding efficient solutions that address the interplay between data management, algorithmic and visual analysis tools is challenging. I will discuss some of these challenges and demonstrate how we are addressing them in our Refinery Platform project (http://www.refinery-platform.org).
The international Symposium on Biological Data Visualization (BioVis) is an interdisciplinary event covering all aspects of visualization in biology. The Symposium brings together researchers from the visualization, bioinformatics, and biology communities with the purpose of educating, inspiring, and engaging visualization researchers in problems in biological data visualization as well as bioinformatics and biology researchers in state-of-the-art visualization research. In order to further engage with a biological audience, the fourth and fifth editions were organized in collaboration with the International Society for Computational Biology and held jointly with their ISMB annual conference.
We are keen to maintain a presence with the VIS community and this meetup will serve as a focus for researchers in BioVis to meet up at VIS to discuss ideas for further development of the Biological Visualisation Community. In particular, this meetup will bring together BioVis researchers and groups of interest within the City of Chicago, who runs a regular Data Visualization Meetup in Chicago. Website: http://www.meetup.com/The-Chicago-Data-Visualization-Group/
Visualization Approaches for Biomedical Omics Data: Putting It All TogetherNils Gehlenborg
Keynote Talk presented at the 1st Annual BiVi Community Annual Meeting (17 December 2014)
http://bivi.co/page/bivi-annual-meeting-16-17th-december-2014
Visualization Approaches for Biomedical Omics Data: Putting It All Together
The rapid proliferation of high quality, low cost genome-wide measurement technologies such as whole-genome and transcriptome sequencing, as well as advances in epigenomics and proteomics, are enabling researchers to perform studies that generate heterogeneous datasets for cohorts of thousands of individuals. A common feature of these studies is that a collection of genome-wide, molecular data types and phenotypic or clinical characterizations are available for each individual. These data can be used to identify the molecular basis of diseases and to characterize and describe the variations that are relevant for improved diagnosis, prognosis and targeted treatment of patients. An example for a study in which this approach has been successfully applied is The Cancer Genome Atlas project (http://cancergenome.nih.gov).
In my talk I will discuss how visualization approaches can be applied to enable exploration and support analysis of data generated by such studies. Specifically, I will review techniques and tools for visual exploration of individual omics data types, their ability to scale to large numbers of individuals or samples, and emerging techniques that integrate multiple omics data types for interactive visual analysis. I will also examine technical and legal challenges that developers of such visualization tools are facing. To conclude my talk, I will outline research opportunities for the biological data visualization community that address major challenges in this domain.
Guided visual exploration of patient stratifications in cancer genomicsNils Gehlenborg
Talk presented at the "Beyond the Genome 2014: Cancer Genomics" conference (10 October 2014)
http://www.beyond-the-genome.com/2014/
Cancer is a heterogeneous disease, and molecular profiling of tumors from large cohorts has enabled characterization of new tumor subtypes. This is a prerequisite for improving personalized treatment and ultimately better patient outcomes. Potential tumor subtypes can be identified with methods such as unsupervised clustering or network-based stratification, which assign patients to sets based on high-dimensional molecular profiles. Detailed characterization of identified sets and their interpretation, however, remain a time-consuming exploratory process.
To address these challenges, we have developed StratomeX (http://stratomex.caleydo.org), an interactive visualization tool that complements algorithmic approaches. StratomeX also integrates a computational framework for query-based guided exploration directly into the visualization, enabling discovery of novel relationships between patient sets and efficient generation and refinement of hypotheses about tumor subtypes. StratomeX enables analysts to efficiently compare multiple patient stratifications, to correlate patient sets with clinical information or genomic alterations, and to view the differences between molecular profiles across patient sets.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Data Visualization in Biomedical Sciences: More than Meets the Eye
1. Data Visualization in Biomedical Sciences:
More than Meets the Eye
Nils Gehlenborg, PhD
Department of Biomedical Informatics
Harvard Medical School
http://gehlenborglab.org @ngehlenborghttp://gehlenborglab.org
4. Data Visualization in Biomedical Sciences:
More than Meets the Eye
Nils Gehlenborg, PhD
Department of Biomedical Informatics
Harvard Medical School
http://gehlenborglab.org @ngehlenborghttp://gehlenborglab.org
22. Nature asked 1,576 researchers if there
is a reproducibility crisis in science.
M Baker, Nature 533, 452-454, 2016
23. 0% 100%
No crisis (3%)
Don’t know (7%)
Slight crisis (38%)
M Baker, Nature 533, 452-454, 2016
Significant crisis (52%)
Nature asked 1,576 researchers if there
is a reproducibility crisis in science.
28. Intentional?
Inability to capture everything?
Inability to communicate everything?
SOCIAL ISSUE
TECHNICAL ISSUES
M Baker, Nature 533, 452-454, 2016
30. Tumor Subtypes
PROBLEM 1
Visualize overlap of patient sets across two or more stratifications.
PROBLEM 2
Visualize characteristics of patient sets within a stratification of interest.
33. Tumor Subtypes
PROBLEM 1
Visualize overlap of patient sets across two or more stratifications.
PROBLEM 2
Visualize characteristics of patient sets within a stratification of interest.
PROBLEM 3
Identify relevant stratifications, pathways, and clinical variables.
34. Is there a mutation that overlaps with this mRNA cluster?
Is there a CNV that affects survival?
Is there a pathway that is enriched in this cluster?
Is there a mutually exclusive mutation?
Query
Stratifications
Clinical Params
Pathways
Guided
Exploration
M Streit, A Lex, S Gratzl, C Partl, D Schmalstieg, H Pfister, P Park, N Gehlenborg , Nature Methods (2014)