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2016 | OriginalPaper | Chapter

Identification of Hot Regions in Protein-Protein Interactions Based on Detecting Local Community Structure

Authors : Xiaoli Lin, Xiaolong Zhang

Published in: Intelligent Computing Theories and Application

Publisher: Springer International Publishing

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Abstract

Hot regions can help proteins to exert their biological function and contribute to understand the molecular mechanism, which is the foundation of drug designs. In this paper, combining protein biological characteristics, a new method is proposed to predict protein hot regions. Firstly, we used support vector machine to predict the hot spots. Then, the local community structure detecting algorithm based on the identification of boundary nodes was proposed to predict the hot regions in protein-protein interactions. The experimental results demonstrate that the proposed method improves significantly the predictive accuracy and performance of protein hot regions.

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previous chapter Prediction of Hot Spots Based on Physicochemical Features and Relative Accessible Surface Area of Amino Acid Sequence
next chapter Power Spectrum-Based Genomic Feature Extraction from High-Throughput ChIP-seq Sequences
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Metadata
Title
Identification of Hot Regions in Protein-Protein Interactions Based on Detecting Local Community Structure
Authors
Xiaoli Lin
Xiaolong Zhang
Copyright Year
2016
Book
Intelligent Computing Theories and Application

Print ISBN: 978-3-319-42290-9

Electronic ISBN: 978-3-319-42291-6

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-42291-6_43

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