A5053171726- Biomedical Text Mining and Ontologies
- Semantic Web and Ontologies
- Bioinformatics and Genomic Networks
- Natural Language Processing Techniques
- Service-Oriented Architecture and Web Services
- Genomics and Phylogenetic Studies
- Genomics and Rare Diseases
- vaccines and immunoinformatics approaches
- Cell Image Analysis Techniques
- linguistics and terminology studies
- Computational Drug Discovery Methods
- Genetics, Bioinformatics, and Biomedical Research
- Influenza Virus Research Studies
- Business Process Modeling and Analysis
- Research Data Management Practices
- Cancer-related molecular mechanisms research
- SARS-CoV-2 and COVID-19 Research
- RNA and protein synthesis mechanisms
- Algorithms and Data Compression
- Ethics in Clinical Research
- Machine Learning in Bioinformatics
- Music Technology and Sound Studies
- Complex Network Analysis Techniques
- Digital Filter Design and Implementation
- Single-cell and spatial transcriptomics
University at Buffalo, State University of New York
2013-2024
Fred Hutch Cancer Center
2014
Stanford University
2014
Simon Fraser University
2014
National Institutes of Health
2014
Cancer Research Center
2014
J. Craig Venter Institute
2014
Duke University
2013
Georgetown University
2013
Georgetown University Medical Center
2013
The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies provide a representation biomedical knowledge from Open Biological Ontologies (OBO) project adds ability this was derived. We here state several applications using it, such as adding semantic expressivity existing databases, building data entry forms,...
Experimental descriptions are typically stored as free text without using standardized terminology, creating challenges in comparison, reproduction and analysis. These difficulties impose limitations on data exchange information retrieval.
The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, CL has undergone multiple rounds revision and expansion, most notably representation hematopoietic cells. For vivo cells, focuses on vertebrates but provides general classes that can be used for other metazoans, which subtyped species-specific ontologies. Recent work focused extending various types, developing new modules itself, related...
Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack community-wide, consensus-based, human- machine-interpretable language for describing phenotypes genomic environmental contexts is perhaps most pressing scientific bottleneck integration across many key fields in biology, including genomics, systems development, medicine, evolution, ecology, systematics. Here we survey phenomics...
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...
Ontology development is a rapidly growing area of research, especially in the life sciences domain. To promote collaboration and interoperability between different projects, OBO Foundry principles require that these ontologies be open non-redundant, avoiding duplication terms through re-use existing resources. As current options to do so present various difficulties, new approach, MIREOT, allows specifying import single terms. Initial implementations allow for controlled selected annotations...
While the Web Ontology Language (OWL) provides a mechanism to import ontologies, this is not always suitable. Current editing tools present challenges for working with large ontologies and direct OWL imports can prove impractical day-to
Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information Description Frameworks (RDFs) HTTP. Ontologies, which logically represent relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology server that stores RDF triple store technology supports query, visualization linkage terms. also default for publishing browsing biomedical ontologies Open Biological...
The Protein Ontology (PRO; http://purl.obolibrary.org/obo/pr) formally defines and describes taxon-specific taxon-neutral protein-related entities in three major areas: proteins related by evolution; produced from a given gene; protein-containing complexes. PRO thus serves as tool for referencing protein at any level of specificity. To enhance this ability, to facilitate the comparison such described different resources, we developed standardized representation proteoforms using UniProtKB...
Basic Formal Ontology (BFO) is a top-level ontology consisting of thirty-six classes, designed to support information integration, retrieval, and analysis across all domains scientific investigation, presently employed in over 350 projects around the world. BFO genuine ontology, containing no terms particular material domains, such as physics, medicine, or psychology. In this paper, we demonstrate how series cases illustrating common types change may be represented by universals, defined...
Translational research, the effort to couple results of basic research clinical applications, depends on ability effectively answer questions using information that spans multiple disciplines. The Semantic Web, with its emphasis combining standard representation languages, access via web protocols, and technologies leverage computation, such as in form inference distributable query, offers a social technological basis for assembling, integrating making available biomedical knowledge at Web...
The Protein Ontology (PRO; http://proconsortium.org) formally defines protein entities and explicitly represents their major forms interrelations. represented in PRO corresponding to single amino acid chains are categorized by level of specificity into family, gene, sequence modification metaclasses, there is a separate metaclass for complexes. All metaclasses also have organism-specific derivatives. complements established databases such as UniProtKB, interoperates with other biomedical...
Abstract Background We are developing the Neurological Disease Ontology (ND) to provide a framework enable representation of aspects neurological diseases that relevant their treatment and study. ND is representational tool addresses need for unambiguous annotation, storage, retrieval data associated with study diseases. being developed in compliance Open Biomedical Foundry principles builds upon paradigm established by General Medical Science (OGMS) entities domain disease medical practice....
Abstract Motivation: Advancing our understanding of how nervous systems work will require the ability to store and annotate 3D anatomical datasets, recording morphology, partonomy connectivity at multiple levels granularity from subcellular gross anatomy. It also integrate this data with other data-types including functional, genetic electrophysiological data. The web ontology language OWL2 provides means solve many these problems. Using it, one can rigorously define relate classes structure...
As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, cross-reference miRNA-target interactions better explore delineate functions. Semantic technologies can help this regard. We previously developed domain-specific application ontology, Ontology for MIcroRNA Target...
The translational research community, in general, and the Clinical Translational Science Awards (CTSA) particular, share vision of repurposing EHRs for that will improve quality clinical practice. Many members these communities are also aware electronic health records (EHRs) suffer limitations data becoming poorly structured, biased, unusable out original context. This creates obstacles to continuity care, utility, improvement, research. Analogous sharing objective other areas natural...