| Literature DB >> 25609570 |
Chenglin Liu1, Jing Su, Fei Yang, Kun Wei, Jinwen Ma, Xiaobo Zhou.
Abstract
The Library of Integrated Network-based Cellular Signatures (LINCS) L1000 big data provide gene expression profiles induced by over 10 000 compounds, shRNAs, and kinase inhibitors using the L1000 platform. We developed csNMF, a systematic compound signature discovery pipeline covering from raw L1000 data processing to drug screening and mechanism generation. The csNMF pipeline demonstrated better performance than the original L1000 pipeline. The discovered compound signatures of breast cancer were consistent with the LINCS KINOMEscan data and were clinically relevant. The csNMF pipeline provided a novel and complete tool to expedite signature-based drug discovery leveraging the LINCS L1000 resources.Entities:
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Year: 2015 PMID: 25609570 PMCID: PMC4333019 DOI: 10.1039/c4mb00677a
Source DB: PubMed Journal: Mol Biosyst ISSN: 1742-2051