Literature DB >> 25609570

Compound signature detection on LINCS L1000 big data.

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.

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Year:  2015        PMID: 25609570      PMCID: PMC4333019          DOI: 10.1039/c4mb00677a

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


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