Kent Shefchek
A5050786158- Biomedical Text Mining and Ontologies
- Genomics and Rare Diseases
- Bioinformatics and Genomic Networks
- Genetics, Bioinformatics, and Biomedical Research
- Research Data Management Practices
- Semantic Web and Ontologies
- Genomic variations and chromosomal abnormalities
- Immunodeficiency and Autoimmune Disorders
- Advanced Graph Neural Networks
- Glycosylation and Glycoproteins Research
- Chronic Lymphocytic Leukemia Research
- Topic Modeling
- Microbial Metabolites in Food Biotechnology
- Infectious Diseases and Mycology
- Legume Nitrogen Fixing Symbiosis
- Gastric Cancer Management and Outcomes
- Genomics and Phylogenetic Studies
- Tuberculosis Research and Epidemiology
- Nutrition, Genetics, and Disease
- Gene expression and cancer classification
- Wastewater Treatment and Nitrogen Removal
- Helicobacter pylori-related gastroenterology studies
- Mycobacterium research and diagnosis
- Microbial Community Ecology and Physiology
- BRCA gene mutations in cancer
Oregon State University
2019-2024
University of Colorado Anschutz Medical Campus
2022-2023
Oregon Health & Science University
2015-2022
Helix (United States)
2022
Oregon Clinic
2018
University of Maryland, Baltimore
2012-2013
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...
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 There are thousands of distinct disease entities and concepts, each which known by different sometimes contradictory names. The lack a unified system for managing these poses major challenge both machines humans that need to harmonize information better predict causes treatments disease. Mondo Disease Ontology is an open, community-driven ontology integrates key medical biomedical terminologies, supporting data integration improve diagnosis, treatment, translational research....
Abstract Despite progress in the development of standards for describing and exchanging scientific information, lack easy-to-use mapping between different representations same or similar objects databases poses a major impediment to data integration interoperability. Mappings often metadata needed be correctly interpreted applied. For example, are two terms equivalent merely related? Are they narrow broad matches? Or associated some other way? Such relationships mapped not documented, which...
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...
Enterobacter radicincitans sp. nov. DSM16656(T) represents a new species of the genus which is biological nitrogen-fixing endophytic bacterium with growth-promoting effects on variety crop and model plant species. The presence genes for nitrogen fixation, phosphorous mobilization, phytohormone production reflects this microbe's potential activity.
The Matchmaker Exchange application programming interface (API) allows searching a patient's genotypic or phenotypic profiles across clinical sites, for the purposes of cohort discovery and variant disease causal validation. This API can be used not only to search matching patients, but also match against public model organism data. data enable known diseases variant-phenotype associations using phenotype semantic similarity algorithms developed by Monarch Initiative. provide additional...
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.
ABSTRACT Mycobacterium massiliense ( abscessus group) is an emerging pathogen causing pulmonary disease and skin soft tissue infections. We report the genome sequence of type strain CCUG 48898.
Helicobacter pylori , inhabitant of the gastric mucosa over half world population, with decreasing prevalence in U.S., has been associated a variety pathologies. However, majority H. -infected individuals remain asymptomatic, and negative correlations between allergic diseases have reported. Comprehensive genome characterization populations from different human host backgrounds including healthy provides exciting potential to generate new insights into open question whether health outcome is...
Abstract The principles of genetics apply across the whole tree life: on a cellular level, we share mechanisms with species from which diverged millions or even billions years ago. We can exploit this common ancestry at level sequences, but also in terms observable outcomes (phenotypes), to learn more about health and disease for humans all other species. Applying range available knowledge solve challenging problems requires unified data relating genomics, phenotypes, disease; it...
Background 16p13.11 microduplication syndrome has a variable presentation and is characterized primarily by neurodevelopmental physical phenotypes resulting from copy number variation at chromosome 16p13.11. Given its variability, there may be features that have not yet been reported. The goal of this study was to use patient “self-phenotyping” survey collect data directly patients further characterize the syndrome. Objective This aimed (1) discover self-identified in underrepresented...
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 Deep phenotyping is important for improving diagnostics and rare diseases research especially effective when standardized using Human Phenotype Ontology (HPO). Patients are an under-utilized source of information, so to facilitate self-phenotyping we previously “translated” HPO into plain language (“layperson HPO”). Another survey, GenomeConnect, asks patient-friendly questions that map HPO. However, self-reported data has not been assessed. Since all terms translated layperson or...
Despite progress in the development of standards for describing and exchanging scientific information, lack easy-to-use mapping between different representations same or similar objects databases poses a major impediment to data integration interoperability. Mappings often metadata needed be correctly interpreted applied. For example, are two terms equivalent merely related? Are they narrow broad matches? associated some other way? Such relationships mapped not documented, leading incorrect...
Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph-based data models elucidate the interconnectedness between core biomedical concepts, enable structures to be easily updated, support intuitive queries, visualizations, inference algorithms. However, discovery across these "knowledge graphs" (KGs) has remained difficult. Data set heterogeneity complexity; proliferation ad hoc formats; poor compliance...
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 knowledge is lacking. Here we present KG-Hub, platform that enables standardized construction, exchange, reuse graphs. Features include simple, modular extract-transform-load (ETL) pattern producing compliant with Biolink Model (a high-level model standardizing biological...