Multiomics Provider
The Multiomics Provider Team provides multiple KPs. We extract knowledge graphs from public datasets, multiomics datasets from the Institute for Systems Biology (ISB), and clinical information from cancer, wellness and EHR datasets. We focus on gene interactions in different tissues or diseases, extend gene-gene interaction to gene-drug association as well as gene-disease associations, and derive correlations and disease risk associations from wellness data and electronic health records.
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Clinical Connections KP: Provides knowledge derived from machine-learning risk models, which were developed on real-world-evidence from 20,000,000 electronic health records (EHRs) across five states. Node types include diseases, drugs, and labs. Edges include predicates for association.
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BigGIM Drug Response KP: Presents associations between mutated genes and drug sensitivity (IC50) in different tumor types using the GDSC dataset (Francesco Iorio et al., Cell, 2016). It features with nodes as Gene.mut and Drug, and edges as associated with sensitivity of or associated with resistance of.
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Wellness KP: Presents significant statistical correlations between blood analytes as measured in a cohort of largely healthy individuals.
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Clinical Trials KP: ClinicalTrials.gov: Presents conditions/diseases and interventions (including drugs) that were tested as part of a clinical trial registered in ClinicalTrials.gov.
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Drug Approvals KP: Presents assertions about regulatory approvals of drug interventions for treating diseases, and observations of off-label use of drug interventions.
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Microbiome KP: Presents relationships bridging various microbiome taxa and microbial pathways with host health.
Overall: Gwênlyn Glusman (gglusman@isbscience.org)
Clinical Connections KP: Jennifer Hadlock (jhadlock@isbscience.org)
BigGIM-DrugResponse KP: Guangrong Qin (gqin@isbscience.org)
All "Big GIM I", "Big GIM II: Drug Response KP" and "Big GIM II: Tumor gene mutation KP" will be combined to a single endpoint, same as the Big GIM II: Drug Response KP.
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Big GIM I function interaction data for all pairs of genes. Data from four different sources: 1) tissue-specific gene expression correlations from healthy tissue samples (GTEx), 2) tissue-specific gene expression correlations from cancer samples (TCGA), 3) tissue-specific probabilities of function interaction (GIANT), and 4) direct interactions (BioGRID).
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Big CLAM (Cell Line Association Miner), integrates large-scale high-quality data from various cell line resources to uncover associations between genomic and molecular features of cell lines, drug response measurements and gene knockdown viability scores. Data comes from five different sources: 1) CCLE - Cancer Cell Line Encyclopedia, 2) GDSC - Genomics of Drug Sensitivity in Cancer, 3) CTRP - Cancer Therapeutics Response Portal, 4) CMap - Connectivity Map, and 5) CDM - Cancer Dependency Map.
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Big GIM I, old version
- Smart API: http://biggim.ncats.io/api
https://docs.google.com/document/d/1ti6yOzokQ6lt4GD-fc0yGyFfRXSDQ-UG0mkn26P0ynU/edit
It should be all here! If something is missing, please contact us.