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Data Mining for Systems Biology

Methods and Protocols

  • Book
  • © 2018

Overview

Editors:
  1. Hiroshi Mamitsuka

    1. Bioinformatics Center, Kyoto University, Uji, Japan

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  • Includes cutting-edge techniques for data mining in systems biology
  • Provides step-by-step guidance essential for reproducible results
  • Contains expert tips and implementation advice from practitioners in the field

Part of the book series: Methods in Molecular Biology (MIMB, volume 1807)

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Table of contents (17 protocols)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Identifying Bacterial Strains from Sequencing Data

    • Tommi Mäklin, Jukka Corander, Antti Honkela
    Pages 1-7

  3. MetaVW: Large-Scale Machine Learning for Metagenomics Sequence Classification

    • Kévin Vervier, Pierre Mahé, Jean-Philippe Vert
    Pages 9-20

  4. Online Interactive Microbial Classification and Geospatial Distributional Analysis Using BioAtlas

    • Jesper Lund, Qihua Tan, Jan Baumbach
    Pages 21-35

  5. Generative Models for Quantification of DNA Modifications

    • Tarmo Äijö, Richard Bonneau, Harri Lähdesmäki
    Pages 37-50

  6. DiMmer: Discovery of Differentially Methylated Regions in Epigenome-Wide Association Study (EWAS) Data

    • Tobias Frisch, Jonatan Gøttcke, Richard Röttger, Qihua Tan, Jan Baumbach
    Pages 51-62

  7. Implementing a Transcription Factor Interaction Prediction System Using the GenoMetric Query Language

    • Stefano Perna, Arif Canakoglu, Pietro Pinoli, Stefano Ceri, Limsoon Wong
    Pages 63-81

  8. Multiple Testing Tool to Detect Combinatorial Effects in Biology

    • Aika Terada, Koji Tsuda
    Pages 83-94

  9. SiBIC: A Tool for Generating a Network of Biclusters Captured by Maximal Frequent Itemset Mining

    • Kei-ichiro Takahashi, David A. duVerle, Sohiya Yotsukura, Ichigaku Takigawa, Hiroshi Mamitsuka
    Pages 95-111

  10. Computing and Visualizing Gene Function Similarity and Coherence with NaviGO

    • Ziyun Ding, Qing Wei, Daisuke Kihara
    Pages 113-130

  11. Analyzing Glycan-Binding Profiles Using Weighted Multiple Alignment of Trees

    • Kiyoko F. Aoki-Kinoshita
    Pages 131-140

  12. Analysis of Fluxomic Experiments with Principal Metabolic Flux Mode Analysis

    • Sahely Bhadra, Juho Rousu
    Pages 141-161

  13. Analyzing Tandem Mass Spectra Using the DRIP Toolkit: Training, Searching, and Post-Processing

    • John T. Halloran
    Pages 163-180

  14. Sparse Modeling to Analyze Drug–Target Interaction Networks

    • Yoshihiro Yamanishi
    Pages 181-193

  15. DrugE-Rank: Predicting Drug-Target Interactions by Learning to Rank

    • Jieyao Deng, Qingjun Yuan, Hiroshi Mamitsuka, Shanfeng Zhu
    Pages 195-202

  16. MeSHLabeler and DeepMeSH: Recent Progress in Large-Scale MeSH Indexing

    • Shengwen Peng, Hiroshi Mamitsuka, Shanfeng Zhu
    Pages 203-209

  17. Disease Gene Classification with Metagraph Representations

    • Sezin Kircali Ata, Yuan Fang, Min Wu, Xiao-Li Li, Xiaokui Xiao
    Pages 211-224

  18. Inferring Antimicrobial Resistance from Pathogen Genomes in KEGG

    • Minoru Kanehisa
    Pages 225-239

  19. Back Matter

    Pages 241-243
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Keywords

About this book

This fully updated book collects numerous data mining techniques, reflecting the acceleration and diversity of the development of data-driven approaches to the life sciences. The first half of the volume examines genomics, particularly metagenomics and epigenomics, which promise to deepen our knowledge of genes and genomes, while the second half of the book emphasizes metabolism and the metabolome as well as relevant medicine-oriented subjects. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that is useful for getting optimal results. 

Authoritative and practical, Data Mining for Systems Biology: Methods and Protocols, Second Edition serves as an ideal resource for researchers of biology and relevant fields, such as medical, pharmaceutical, and agricultural sciences, as well as for the scientists and engineers who are working on developing data-driven techniques, such as databases, data sciences, data mining, visualization systems, and machine learning or artificial intelligence that now are central to the paradigm-altering discoveries being made with a higher frequency.

Editors and Affiliations

  • Bioinformatics Center, Kyoto University, Uji, Japan

    Hiroshi Mamitsuka

Bibliographic Information

  • Book Title: Data Mining for Systems Biology

  • Book Subtitle: Methods and Protocols

  • Editors: Hiroshi Mamitsuka

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-4939-8561-6

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

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

  • Hardcover ISBN: 978-1-4939-8560-9Published: 21 July 2018

  • Softcover ISBN: 978-1-4939-9326-0Published: 10 December 2019

  • eBook ISBN: 978-1-4939-8561-6Published: 21 July 2018

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 2

  • Number of Pages: XI, 243

  • Number of Illustrations: 9 b/w illustrations, 86 illustrations in colour

  • Topics: Bioinformatics

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