Computational Prediction of Protein Complexes from Protein Interaction Networks. Sriganesh Srihari
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 1 | Introduction 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 2 | Constructing 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 3 | Computational 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 4 | Evaluating 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 5 | Open 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 6 | Identifying 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 7 | Identifying Evolutionarily Conserved Protein Complexes |
| 7.1 Inferring Evolutionarily Conserved PPIs (Interologs) | |
| 7.2 Identifying Conserved Complexes from Interolog Networks, I | |
| 7.3 Identifying Conserved Complexes from Interolog Networks, II | |
| Chapter 8 | Protein Complex Prediction in the Era of Systems Biology |
| 8.1 Constructing the Network of Protein Complexes | |
| 8.2 Identifying Protein Complexes Across Phenotypes | |
| 8.3 Identifying Protein Complexes in Diseases | |
| 8.4 Enhancing Quantitative Proteomics Using PPI Networks and Protein Complexes | |
| 8.5 Systems Biology Tools and Databases to Analyze Biomolecular Networks | |
| Chapter 9 | Conclusion |
| References | |
| Authors’ Biographies |
Preface
The suggestion and motivation to write this book came from Limsoon, who thought that it would be a great idea to compile our (Sriganesh’s and Chern Han’s) Ph.D. research conducted at National University of Singapore on protein complex prediction from protein-protein interaction (PPI) networks into a comprehensive book for the research community. Since we (Sriganesh and Chern Han) completed our Ph.D.s not long ago, the timing could not have been better for writing this book while the topic is still fresh in our minds and the empirical set up (datasets and software pipelines) for evaluating the methods is still in a “quick-to-run” form. However, although we had our Ph.D. theses to our convenient disposal and reference, it is only after we started writing this book that we realized the real scale of the task that we had embarked upon.
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