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Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data: Drug Association Networks

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Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data : Drug Association Networks. / Musa, Aliyu; Tripathi, Shailesh; Dehmer, Matthias; Yli-Harja, Olli; Kauffman, Stuart A.; Emmert-Streib, Frank.

In: Scientific Reports, Vol. 9, No. 1, 7849, 24.05.2019.

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Musa, Aliyu ; Tripathi, Shailesh ; Dehmer, Matthias ; Yli-Harja, Olli ; Kauffman, Stuart A. ; Emmert-Streib, Frank. / Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data : Drug Association Networks. In: Scientific Reports. 2019 ; Vol. 9, No. 1.

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@article{3b26eb8fb1eb448785e1ce71a6ff5511,
title = "Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data: Drug Association Networks",
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.",
author = "Aliyu Musa and Shailesh Tripathi and Matthias Dehmer and Olli Yli-Harja and Kauffman, {Stuart A.} and Frank Emmert-Streib",
note = "EXT={"}Kauffman, Stuart A.{"} EXT={"}Tripathi, Shailesh{"}",
year = "2019",
month = "5",
day = "24",
doi = "10.1038/s41598-019-44291-3",
language = "English",
volume = "9",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data

T2 - Drug Association Networks

AU - Musa, Aliyu

AU - Tripathi, Shailesh

AU - Dehmer, Matthias

AU - Yli-Harja, Olli

AU - Kauffman, Stuart A.

AU - Emmert-Streib, Frank

N1 - EXT="Kauffman, Stuart A." EXT="Tripathi, Shailesh"

PY - 2019/5/24

Y1 - 2019/5/24

N2 - 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.

AB - 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.

U2 - 10.1038/s41598-019-44291-3

DO - 10.1038/s41598-019-44291-3

M3 - Article

VL - 9

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 7849

ER -