ArticleScientific reports2019
Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data: Drug Association Networks.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Exploring common mechanisms of adverse drug reactions and disease phenotypes through network-based analysis.Cell reports methods · 2025Article
- PGxDB: an interactive web-platform for pharmacogenomics research.Nucleic acids research · 2025Article
- Donepezil Nanoemulsion Induces a Torpor-like State with Reduced Toxicity in NonhibernatingACS nano · 2024Article
- Accelerating drug discovery and repurposing by combining transcriptional signature connectivity with docking.Science advances · 2024Article
- Drug repurposing screening and mechanism analysis based on human colorectal cancer organoids.Protein & cell · 2024Article
- Predicting cellular responses to complex perturbations in high-throughput screens.Molecular systems biology · 2023Article
- Factor-specific generative pattern from large-scale drug-induced gene expression profile.Scientific reports · 2023Article
- COVID19 Drug Repository: text-mining the literature in search of putative COVID19 therapeutics.Nucleic acids research · 2021Article
- Data-Driven Computational Social Network Science: Predictive and Inferential Models for Web-Enabled Scientific Discoveries.Frontiers in big data · 2021Article
- An Integrated System Biology Approach Yields Drug Repositioning Candidates for the Treatment of Heart Failure.Frontiers in genetics · 2019Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern research in the biomedical sciences is data-driven utilizing high-throughput technologies to generate big genomic data. The Library of Integrated Network-based Cellular Signatures (LINCS) is an example for a large-scale genomic data repository providing hundred thousands of high-dimensional gene expression measurements for thousands of drugs and dozens of cell lines. However, the remaining challenge is how to use these data effectively for pharmacogenomics. In this paper, we use LINCS data to construct drug association networks (DANs) representing the relationships between drugs. By using the Anatomical Therapeutic Chemical (ATC) classification of drugs we demonstrate that the DANs represent a systems pharmacogenomic landscape of drugs summarizing the entire LINCS repository on a genomic scale meaningfully. Here we identify the modules of the DANs as therapeutic attractors of the ATC drug classes.
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