Seth Carbon
A5089928926- Biomedical Text Mining and Ontologies
- Bioinformatics and Genomic Networks
- Genetics, Bioinformatics, and Biomedical Research
- Gene expression and cancer classification
- Genomics and Rare Diseases
- Genomics and Phylogenetic Studies
- Semantic Web and Ontologies
- Research Data Management Practices
- Advanced Graph Neural Networks
- Scientific Computing and Data Management
- Computational Physics and Python Applications
- Banana Cultivation and Research
- Superconducting Materials and Applications
- Big Data Technologies and Applications
- Computational Drug Discovery Methods
- Cell Image Analysis Techniques
- Tuberculosis Research and Epidemiology
- Management, Economics, and Public Policy
- AI in cancer detection
- Cell Adhesion Molecules Research
- Botanical Studies and Applications
- Seismology and Earthquake Studies
- Genetics, Aging, and Longevity in Model Organisms
- Misinformation and Its Impacts
- Digital Imaging for Blood Diseases
Lawrence Berkeley National Laboratory
2016-2025
University College London
2023
University of Padua
2023
SIB Swiss Institute of Bioinformatics
2023
Stanford University
2023
Phoenix Bioinformatics
2023
University at Buffalo, State University of New York
2023
University of Southern California
2023
Ontario Institute for Cancer Research
2011
Joint Genome Institute
2008
The Gene Ontology resource (GO; http: //geneontology.org)provides structured, computable knowledge regarding the functions of genes and gene products.Founded in 1998, GO has become widely adopted life sciences, its contents are under continual improvement, both quantity quality.Here, we report major developments during past two years.Each monthly release is now packaged given a unique identifier (DOI), enabling GO-based analyses on specific to be reproduced future.The molecular function...
Abstract The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding functions of genes and gene products. Here, we report advances consortium over past two years. new GO-CAM annotation framework was notably improved, formalized model with a computational schema to check validate rapidly increasing repository 2838 GO-CAMs. In addition, describe impacts several collaborations refine GO 10% increase in number annotations,...
AmiGO is a web application that allows users to query, browse and visualize ontologies related gene product annotation (association) data. can be used online at the Gene Ontology (GO) website access data provided by GO Consortium; it also downloaded installed local annotations. free open source software developed maintained Consortium.
The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over past year, GOC has implemented several processes to increase quantity, quality and specificity GO annotations. First, number manual, literature-based annotations grown at an increasing rate. Second, as result new 'phylogenetic annotation' process, manually reviewed, homology-based...
The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants be genes that have been characterized, model organisms recapitulate human or veterinary filling evolutionary gaps difficult, many resources must queried to find potentially significant genotype–phenotype associations. Non-human proven instrumental revealing...
Abstract In biology and biomedicine, relating phenotypic outcomes with genetic variation environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants be in genes that haven’t been characterized, research organisms recapitulate human or veterinary affecting disease are unknown undocumented, many resources must queried to find potentially significant associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on...
Abstract The Alliance of Genome Resources (Alliance) is a consortium the major model organism databases and Gene Ontology that guided by vision facilitating exploration related genes in human well-studied organisms providing highly integrated comprehensive platform enables researchers to leverage extensive body genetic genomic studies these organisms. Initiated 2016, building central portal (www.alliancegenome.org) for access data primary along with gene ontology data. All types represented...
Biological ontologies are used to organize, curate and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple can be problematic, as they developed independently, which lead incompatibilities. The Open Biomedical Ontologies (OBO) Foundry was created address by facilitating development, harmonization, application sharing ontologies, guided set overarching principles. One challenge in reaching these...
Abstract The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference supporting genomic analyses through semantic similarity machine learning algorithms. HPO has widespread applications in clinical diagnostics translational research, including diagnostics, gene-disease discovery, cohort analytics. In recent years, groups around world have developed translations from English...
The Alliance of Genome Resources (the Alliance) is a combined effort 7 knowledgebase projects: Saccharomyces Database, WormBase, FlyBase, Mouse the Zebrafish Information Network, Rat and Gene Ontology Resource. seeks to provide several benefits: better service various communities served by these projects; harmonized view data for all biomedical researchers, bioinformaticians, clinicians, students; more sustainable infrastructure. has cross-organism useful comparative views gene function,...
Abstract The Alliance of Genome Resources (Alliance) is an extensible coalition knowledgebases focused on the genetics and genomics intensively studied model organisms. organized as individual knowledge centers with strong connections to their research communities a centralized software infrastructure, discussed here. Model organisms currently represented in are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, rat, Gene Ontology Consortium. project rapid...
The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies. number GO annotations products has increased due to curation efforts among Consortium (GOC) groups, including focused literature-based annotation and ortholog-based functional inference. ontologies continue expand improve as result targeted ontology development, introduction computable logical definitions...
The Gene Ontology (GO) is a collaborative effort that provides structured vocabularies for annotating the molecular function, biological role, and cellular location of gene products in highly systematic way species-neutral manner with aim unifying representation function across different organisms. Each contributing member GO Consortium independently associates terms to from organism(s) they are annotating. Here we introduce Reference Genome project, which brings together those independent...
The Planteome project (http://www.planteome.org) provides a suite of reference and species-specific ontologies for plants annotations to genes phenotypes. Ontologies serve as common standards semantic integration large growing corpus plant genomics, phenomics genetics data. include the Plant Ontology, Trait Ontology Experimental Conditions developed by project, along with Gene Chemical Entities Biological Interest, Phenotype Attribute others. also access Crop various breeding research...
In an effort to comprehensively characterize the functional elements within genomes of important model organisms Drosophila melanogaster and Caenorhabditis elegans, NHGRI organism Encyclopaedia DNA Elements (modENCODE) consortium has generated enormous library genomic data along with detailed, structured information on all aspects experiments. The modMine database (http://intermine.modencode.org) described here been built by modENCODE Data Coordination Center allow broader research community...
The Gene Ontology project integrates data about the function of gene products across a diverse range organisms, allowing transfer knowledge from model organisms to humans, and enabling computational analyses for interpretation high-throughput experimental clinical data. core structure is annotation, an association between product term one three ontologies comprising GO. Historically, it has not been possible provide additional information context GO term, such as target or location molecular...
Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to pandemic by biomedical research community. While rich biological knowledge exists related viruses (SARS-CoV, MERS-CoV), integrating this difficult time-consuming, since much of it in siloed databases or textual format. Furthermore, required community vary drastically different tasks; optimal a machine learning task, example, from used populate browsable user interface clinicians. To address these...
Abstract Similar to managing software packages, the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking and dependency management. To manage these processes, a diverse set of tools is required, from command-line utilities powerful ontology-engineering environmentsr. Particularly in biomedical domain, which has developed highly yet inter-dependent ontologies, standardizing release practices metadata establishing shared...
Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing ontologies, semantic models, knowledge graphs translational research. App an integrated platform combining about genes, phenotypes, diseases across species. Monarch's APIs enable access to carefully...
The principles of genetics apply across the entire tree life. At cellular level we share biological mechanisms with species from which diverged millions, even billions years ago. We can exploit this common ancestry to learn about health and disease, by analyzing DNA protein sequences, but also through observable outcomes genetic differences, i.e. phenotypes. To solve challenging disease problems need unify heterogeneous data that relates genomics traits. Without a big-picture view phenotypic...
Abstract A comprehensive, computable representation of the functional repertoire all macromolecules encoded within human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating structured body information about gene functions, which now includes experimental findings reported in more than 175,000 publications genes experimentally tractable model organisms 1,2 . Here, we describe results large,...
Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology many other domains, but coherent solution constructing, exchanging, facilitating the downstream use of KGs is lacking.