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Omics Data Integration and Analysis for Systems Pharmacology

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Bioinformatics and Drug Discovery

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1939))

Abstract

Systems pharmacology aims to understand drug actions on a multi-scale from atomic details of drug-target interactions to emergent properties of biological network and rationally design drugs targeting an interacting network instead of a single gene. Multifaceted data-driven studies, including machine learning-based predictions, play a key role in systems pharmacology. In such works, the integration of multiple omics data is the key initial step, followed by optimization and prediction. Here, we describe the overall procedures for drug-target association prediction using REMAP, a large-scale off-target prediction tool. The method introduced here can be applied to other relation inference problems in systems pharmacology.

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Acknowledgment

We acknowledge Miriam Cohen, Ph.D., for proofreading the manuscript.

Author information

Authors and Affiliations

  1. The Ph.D. Program in Biochemistry, The Graduate Center, The City University of New York, New York, NY, USA

    Hansaim Lim & Lei Xie

  2. Department of Computer Science, Hunter College, The City University of New York, New York, NY, USA

    Lei Xie

Authors
  1. Hansaim Lim
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  2. Lei Xie
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Corresponding author

Correspondence to Lei Xie .

Editor information

Editors and Affiliations

  1. Department of Pathology, University of New Mexico, Albuquerque, NM, USA

    Richard S. Larson

  2. Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA

    Tudor I. Oprea

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Lim, H., Xie, L. (2019). Omics Data Integration and Analysis for Systems Pharmacology. In: Larson, R., Oprea, T. (eds) Bioinformatics and Drug Discovery. Methods in Molecular Biology, vol 1939. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9089-4_11

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  • DOI: https://doi.org/10.1007/978-1-4939-9089-4_11

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-9088-7

  • Online ISBN: 978-1-4939-9089-4

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