A5004252217- Biomedical Text Mining and Ontologies
- Bioinformatics and Genomic Networks
- Genomics and Rare Diseases
- Semantic Web and Ontologies
- Natural Language Processing Techniques
- Scientific Computing and Data Management
- Artificial Intelligence in Healthcare
- Historical Astronomy and Related Studies
- Distributed and Parallel Computing Systems
- Weed Control and Herbicide Applications
- Patient-Provider Communication in Healthcare
- Open Education and E-Learning
- Empathy and Medical Education
- Dental Research and COVID-19
- Historical and Literary Studies
- Plant Pathogens and Fungal Diseases
- Research Data Management Practices
- Theology and Canon Law Studies
- Electronic Health Records Systems
- Healthcare Systems and Technology
- Recycling and Waste Management Techniques
- History of Medicine Studies
- Plant pathogens and resistance mechanisms
- Gene expression and cancer classification
University of Pittsburgh
2010-2016
University of California System
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...
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...
The PaTH (University of Pittsburgh/UPMC, Penn State College Medicine, Temple University Hospital, and Johns Hopkins University) clinical data research network initiative is a collaborative effort among four academic health centers in the Mid-Atlantic region. will provide robust infrastructure to conduct research, explore outcomes, link with biospecimens, improve methods for sharing analyzing across our diverse populations. Our disease foci are idiopathic pulmonary fibrosis, atrial...
Research networking systems hold great promise for helping biomedical scientists identify collaborators with the expertise needed to build interdisciplinary teams. Although efforts date have focused primarily on collecting and aggregating information, less attention has been paid design of end-user tools using these collections collaborators. To be effective, collaborator search must provide researchers easy access information relevant their collaboration needs.The aim was study user...
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...
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...
Patient education plays an important role in the delivery of dental care. Current evidence suggests that emergence Internet and other electronic resources are significantly influencing how patients learn about their healthcare. We conducted a qualitative inquiry using combination interviews with clinicians, direct observation patient episodes, to begin identifying requirements for customized, patient-centered approaches at point Most our study felt comfortable amount method during visit, but...
Tissue microarrays (TMAs) are enormously useful tools for translational research, but incompatibilities in database systems between various researchers and institutions prevent the efficient sharing of data that could help realize their full potential. Resource Description Framework (RDF) provides a flexible method to represent knowledge triples, which take form Subject-Predicate-Object. All resources described using Uniform Identifiers (URIs), global scope. We present an OWL (Web Ontology...