Computational Prediction of Protein Complexes from Protein Interaction Networks. Sriganesh Srihari

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Computational Prediction of Protein Complexes from Protein Interaction Networks - Sriganesh Srihari ACM Books

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       Computational Prediction of Protein Complexes from Protein Interaction Networks

      Sriganesh Srihari, Chern Han Yong, Limsoon Wong

       books.acm.org

       www.morganclaypoolpublishers.com

      ISBN: 978-1-97000-155-6 hardcover

      ISBN: 978-1-97000-152-5 paperback

      ISBN: 978-1-97000-153-2 ebook

      ISBN: 978-1-97000-154-9 ePub

      Series ISSN: 2374-6769 print 2374-6777 electronic

      DOIs:

      10.1145/3064650 Book

      10.1145/3064650.3064651 Preface

      10.1145/3064650.3064652 Chapter 1

      10.1145/3064650.3064653 Chapter 2

      10.1145/3064650.3064654 Chapter 3

      10.1145/3064650.3064655 Chapter 4

      10.1145/3064650.3064656 Chapter 5

      10.1145/3064650.3064657 Chapter 6

      10.1145/3064650.3064658 Chapter 7

      10.1145/3064650.3064659 Chapter 8

      10.1145/3064650.3064660 Chapter 9

      10.1145/3064650.3064661 References, Bios

      A publication in the ACM Books series, #16

      Editor in Chief: M. Tamer Özsu, University of Waterloo

      First Edition

      10 9 8 7 6 5 4 3 2 1

      Dedicated to the Honors, Masters, and Ph.D. students who worked over the years on the different aspects of PPI networks by being part of the computational biology group at the Department of Computer Science, National University of Singapore.

Contents
Preface
Chapter 1Introduction to Protein Complex Prediction
1.1 From Protein Interactions to Protein Complexes
1.2 Databases for Protein Complexes
1.3 Organization of the Rest of the Book
Chapter 2Constructing Reliable Protein-Protein Interaction (PPI) Networks
2.1 High-Throughput Experimental Systems to Infer PPIs
2.2 Data Sources for PPIs
2.3 Topological Properties of PPI Networks
2.4 Theoretical Models for PPI Networks
2.5 Visualizing PPI Networks
2.6 Building High-Confidence PPI Networks
2.7 Enhancing PPI Networks by Integrating Functional Interactions
Chapter 3Computational Methods for Protein Complex Prediction from PPI Networks
3.1 Basic Definitions and Terminologies
3.2 Taxonomy of Methods for Protein Complex Prediction
3.3 Methods Based Solely on PPI Network Clustering
3.4 Methods Incorporating Core-Attachment Structure
3.5 Methods Incorporating Functional Information
Chapter 4Evaluating Protein Complex Prediction Methods
4.1 Evaluation Criteria and Methodology
4.2 Evaluation on Unweighted Yeast PPI Networks
4.3 Evaluation on Weighted Yeast PPI Networks
4.4 Evaluation on Human PPI Networks
4.5 Case Study: Prediction of the Human Mechanistic Target of Rapamycin Complex
4.6 Take-Home Lessons from Evaluating Prediction Methods
Chapter 5Open Challenges in Protein Complex Prediction
5.1 Three Main Challenges in Protein Complex Prediction
5.2 Identifying Sparse Protein Complexes
5.3 Identifying Overlapping Protein Complexes
5.4 Identifying Small Protein Complexes
5.5 Identifying Protein Sub-complexes
5.6 An Integrated System for Identifying Challenging Protein Complexes
5.7 Recent Methods for Protein Complex Prediction
5.8 Identifying Membrane-Protein Complexes
Chapter 6Identifying Dynamic Protein Complexes
6.1 Dynamism of Protein Interactions and Protein Complexes
6.2 Identifying Temporal Protein Complexes
6.3 Intrinsic Disorder in Proteins
6.4 Intrinsic Disorder in Protein Interactions and Protein Complexes
6.5 Identifying Fuzzy Protein Complexes
Chapter 7Identifying Evolutionarily Conserved Protein Complexes
7.1 Inferring Evolutionarily Conserved PPIs (Interologs)
7.2

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