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Computational Chemogenomics

  • Book
  • © 2018

Overview

Editors:
  1. J.B. Brown

    1. Life Science Informatics Research Unit, Laboratory of Molecular Biosciences, Kyoto University Graduate School of Medicine, Kyoto, Japan

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  • Includes cutting-edge methods for computational chemogenomics
  • Provides step-by-step detail essential for reproducible results
  • Contains key notes and implementation advice from the experts

Part of the book series: Methods in Molecular Biology (MIMB, volume 1825)

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Table of contents (15 protocols)

  1. Front Matter

    Pages i-xii
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  2. Data Resources for Computational Chemogenomics

    1. Front Matter

      Pages 1-1
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    2. A Survey of Web-Based Chemogenomic Data Resources

      • Rasel Al Mahmud, Rifat Ara Najnin, Ahsan Habib Polash
      Pages 3-62

    3. Finding Potential Multitarget Ligands Using PubChem

      • Sunghwan Kim, Benjamin A. Shoemaker, Evan E. Bolton, Stephen H. Bryant
      Pages 63-91

  5. Statistical Pattern Recognition

    1. Front Matter

      Pages 353-353
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    2. Linear and Kernel Model Construction Methods for Predicting Drug–Target Interactions in a Chemogenomic Framework

      • Yoshihiro Yamanishi
      Pages 355-368

    3. Selection of Informative Examples in Chemogenomic Datasets

      • Daniel Reker, J. B. Brown
      Pages 369-410

  6. Emerging Topics

    1. Front Matter

      Pages 411-411
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    2. A Platform for Comprehensive Genomic Profiling in Human Cancers and Pharmacogenomics Therapy Selection

      • Tadayuki Kou, Masashi Kanai, Mayumi Kamada, Masahiko Nakatsui, Shigemi Matsumoto, Yasushi Okuno et al.
      Pages 413-424
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Keywords

About this book

This thorough book provides a collection of techniques used in the emerging field of computational chemogenomics, which is an integration of chemoinformatics, bioinformatics, computer science, statistics, automated pattern recognition and modeling, database usage with data retrieval, and systems integration. Beginning with a section on public chemogenomic data resources, the volume continues by delving into the fundamentals of chemoinformatics, bioinformatics, and chemogenomic data processing.  After the reader is comfortable with a core skillset, the volume introduces techniques to analyze specific proteins or compound structures and statistical pattern recognition techniques.  Later chapters describe the future of chemogenomics including applications to medical care. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that serves as an ideal guide in the lab. 

Practical and authoritative, Computational Chemogenomics will greatly aid experimental sciences who are novices to data processing and modeling, as well as those with computationally-oriented backgrounds wishing to engage in this scientific area, which is continually growing and expected to contribute to industry, academic, and government research projects.

Editors and Affiliations

  • Life Science Informatics Research Unit, Laboratory of Molecular Biosciences, Kyoto University Graduate School of Medicine, Kyoto, Japan

    J.B. Brown

Bibliographic Information

  • Book Title: Computational Chemogenomics

  • Editors: J.B. Brown

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-4939-8639-2

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2018

  • Hardcover ISBN: 978-1-4939-8638-5Published: 18 October 2018

  • Softcover ISBN: 978-1-4939-9350-5Published: 10 December 2019

  • eBook ISBN: 978-1-4939-8639-2Published: 17 October 2018

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 1

  • Number of Pages: XII, 454

  • Number of Illustrations: 54 b/w illustrations, 147 illustrations in colour

  • Topics: Bioinformatics

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