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Biological Networks and Pathway Analysis

  • Book
  • © 2017

Overview

Editors:
  1. Tatiana V. Tatarinova

    1. Keck School of Medicine, University of Southern California, Los Angeles, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Yuri Nikolsky

    1. Prosapia Genetics, Solana Beach, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Examines modern tools of OMICs data analysis, both data-driven and knowledge-based
  • Provides real life and research applications of current methods of systems biology by experts in the field
  • Includes specific applications of network and pathway analysis in specific disease areas and personalized medicine
  • Includes supplementary material: sn.pub/extras

Part of the book series: Methods in Molecular Biology (MIMB, volume 1613)

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Table of contents (19 protocols)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. A Practical Guide to Quantitative Interactor Screening with Next-Generation Sequencing (QIS-Seq)

    • Yunchen Gong, Darrell Desveaux, David S. Guttman, Jennifer D. Lewis
    Pages 1-20

  3. sbv IMPROVER: Modern Approach to Systems Biology

    • Svetlana Guryanova, Anna Guryanova
    Pages 21-29

  4. Mathematical Justification of Expression-Based Pathway Activation Scoring (PAS)

    • Alexander M. Aliper, Michael B. Korzinkin, Natalia B. Kuzmina, Alexander A. Zenin, Larisa S. Venkova, Philip Yu. Smirnov et al.
    Pages 31-51

  5. Bioinformatics Meets Biomedicine: OncoFinder, a Quantitative Approach for Interrogating Molecular Pathways Using Gene Expression Data

    • Anton A. Buzdin, Vladimir Prassolov, Alex A. Zhavoronkov, Nikolay M. Borisov
    Pages 53-83

  6. Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks

    • Mark D’Souza, Dinanath Sulakhe, Sheng Wang, Bing Xie, Somaye Hashemifar, Andrew Taylor et al.
    Pages 85-99

  7. Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated “Knowledge-Based” Platform

    • Alexey Dubovenko, Yuri Nikolsky, Eugene Rakhmatulin, Tatiana Nikolskaya
    Pages 101-124

  8. Extracting the Strongest Signals from Omics Data: Differentially Expressed Pathways and Beyond

    • Galina Glazko, Yasir Rahmatallah, Boris Zybailov, Frank Emmert-Streib
    Pages 125-159

  9. Search for Master Regulators in Walking Cancer Pathways

    • Alexander E. Kel
    Pages 161-191

  10. Mathematical Modeling of Avidity Distribution and Estimating General Binding Properties of Transcription Factors from Genome-Wide Binding Profiles

    • Vladimir A. Kuznetsov
    Pages 193-276

  11. A Weighted SNP Correlation Network Method for Estimating Polygenic Risk Scores

    • Morgan E. Levine, Peter Langfelder, Steve Horvath
    Pages 277-290

  12. Analysis of cis-Regulatory Elements in Gene Co-expression Networks in Cancer

    • Martin Triska, Alexander Ivliev, Yuri Nikolsky, Tatiana V. Tatarinova
    Pages 291-310

  13. Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways

    • Rabie Saidi, Imane Boudellioua, Maria J. Martin, Victor Solovyev
    Pages 311-331

  14. ArrayTrack: An FDA and Public Genomic Tool

    • Hong Fang, Stephen C. Harris, Zhenjiang Su, Minjun Chen, Feng Qian, Leming Shi et al.
    Pages 333-353

  15. Identification of Transcriptional Regulators of Psoriasis from RNA-Seq Experiments

    • Alena Zolotarenko, Evgeny Chekalin, Rohini Mehta, Ancha Baranova, Tatiana V. Tatarinova, Sergey Bruskin
    Pages 355-370

  16. Comprehensive Analyses of Tissue-Specific Networks with Implications to Psychiatric Diseases

    • Guan Ning Lin, Roser Corominas, Hyun-Jun Nam, Jorge Urresti, Lilia M. Iakoucheva
    Pages 371-402

  17. Semantic Data Integration and Knowledge Management to Represent Biological Network Associations

    • Sascha Losko, Klaus Heumann
    Pages 403-423

  18. Knowledge-Based Compact Disease Models: A Rapid Path from High-Throughput Data to Understanding Causative Mechanisms for a Complex Disease

    • Anatoly Mayburd, Ancha Baranova
    Pages 425-461

  19. Pharmacologic Manipulation of Wnt Signaling and Cancer Stem Cells

    • Yann Duchartre, Yong-Mi Kim, Michael Kahn
    Pages 463-478

  20. Functional Network Disruptions in Schizophrenia

    • Irina Rish, Guillermo A. Cecchi
    Pages 479-504
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Keywords

About this book

In this volume, expert practitioners present a compilation of methods of functional data analysis (often referred to as “systems biology”) and its applications in drug discovery, medicine, and basic disease research.  It covers such important issues as the elucidation of protein, compound and gene interactions, as well as analytical tools, including networks, interactome and ontologies, and clinical applications of functional analysis.  As a volume in the highly successful Methods in Molecular Biology series, this work provides detailed description and hands-on implementation advice. 

Reputable, comprehensive, and cutting-edge, Biological Networks and Pathway Analysis presents both “wet lab” experimental methods and computational tools in order to cover a broad spectrum of issues in this fascinating new field.

Editors and Affiliations

  • Keck School of Medicine, University of Southern California, Los Angeles, USA

    Tatiana V. Tatarinova

  • Prosapia Genetics, Solana Beach, USA

    Yuri Nikolsky

Bibliographic Information

  • Book Title: Biological Networks and Pathway Analysis

  • Editors: Tatiana V. Tatarinova, Yuri Nikolsky

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-4939-7027-8

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media LLC 2017

  • Hardcover ISBN: 978-1-4939-7025-4Published: 29 August 2017

  • Softcover ISBN: 978-1-4939-8372-8Published: 03 August 2018

  • eBook ISBN: 978-1-4939-7027-8Published: 28 August 2017

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 1

  • Number of Pages: XIV, 509

  • Number of Illustrations: 12 b/w illustrations, 98 illustrations in colour

  • Topics: Protein Science

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