Book chapter
Network Algorithms for Protein Interactions
Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics, pp.355-376
John Wiley & Sons, Inc
10/28/2013
DOI: 10.1002/9781118567869.ch18
Abstract
The task considered in this chapter is to cluster the set of proteins into natural groups that operate together. These groups should be functional groups and can often be identified as serving a particular purpose in the life of a cell. The chapter looks at algorithms for clustering that use optimization methods, often combined with hierarchical methods, as exemplified by the author's work and the work of others. The chapter presents the details of hierarchical algorithms and their performance. Graph theory is commonly used as a method for analyzing protein–protein interactions (PPIs) in computational biology. Each vertex represents a protein, and edges correspond to experimentally identified PPIs. The hierarchical methods discussed here have three main phases: aggregation phase, clustering phase, and disaggregation phase. While there are different coarsening, decoarsening, and clustering algorithms, this framework of optimization‐directed hierarchical methods has found success.
Details
- Title: Subtitle
- Network Algorithms for Protein Interactions
- Creators
- Suely Oliveira
- Contributors
- Yi Pan (Editor) - Georgia State UniversityJianxin Wang (Editor) - Central South UniversityMin Li (Editor) - Central South University
- Resource Type
- Book chapter
- Publication Details
- Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics, pp.355-376
- DOI
- 10.1002/9781118567869.ch18
- Publisher
- John Wiley & Sons, Inc; Hoboken, NJ, USA
- Number of pages
- 21
- Language
- English
- Date published
- 10/28/2013
- Academic Unit
- Computer Science; Mathematics
- Record Identifier
- 9984259461602771
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