Interoperability of Disease Concepts in Clinical and Research Ontologies: Contrasting Coverage and Structure in the Disease Ontology and SNOMED CT.

Objectives: To contrast the coverage of diseases between the Disease Ontology (DO) and SNOMED CT, and to compare the hierarchical structure of the two ontologies.

Methods: We establish a reference list of mappings. We characterize unmapped concepts in DO semantically and structurally.

Extending TCGA queries to automatically identify analogous genomic data from dbGaP.

Data sharing is critical to advance genomic research by reducing the demand to collect new data by reusing and combining existing data and by promoting reproducible research. The Cancer Genome Atlas (TCGA) is a popular resource for individual-level genotype-phenotype cancer related data. The Database of Genotypes and Phenotypes (dbGaP) contains many datasets similar to those in TCGA.

ResearchIQ: Design of a Semantically Anchored Integrative Query Tool.

An important factor influencing the pace of research activity is the ability of researchers to discover and leverage heterogeneous resources. Usually, researcher profiles, laboratory equipment, data samples, clinical trials, and other research resources are stored in heterogeneous datasets in large organizations. Emergent semantic web technologies provide novel approaches to discover, annotate and consequently link such resources.

Real-time Data Fusion Platforms: The Need of Multi-dimensional Data-driven Research in Biomedical Informatics.

Systems designed to expedite data preprocessing tasks such as data discovery, interpretation, and integration that are required before data analysis drastically impact the pace of biomedical informatics research. Current commercial interactive and real-time data integration tools are designed for large-scale business analytics requirements. In this paper we identify the need for end-to-end data fusion platforms from the researcher's perspective, supporting ad-hoc data interpretation and integration.

Conceptual Knowledge Discovery in Databases for Drug Combinations Predictions in Malignant Melanoma.

The worldwide incidence of melanoma is rising faster than any other cancer, and prognosis for patients with metastatic disease is poor. Current targeted therapies are limited in their durability and/or effect size in certain patient populations due to acquired mechanisms of resistance. Thus, the development of synergistic combinatorial treatment regimens holds great promise to improve patient outcomes.