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A new protein graph model for function prediction

Paper ID Volume ID Publish Year Pages File Format Full-Text
15179 1386 2012 5 PDF Available
Title
A new protein graph model for function prediction
Abstract

As several structural proteomic projects are producing an increasing number of protein structures with unknown function, methods that can reliably predict protein functions from protein structures are in urgent need. In this paper, we present a method to explore the clustering patterns of amino acids on the 3-dimensional space for protein function prediction. First, amino acid residues on a protein structure are clustered into spatial groups using hierarchical agglomerative clustering, based on the distance between them. Second, the protein structure is represented using a graph, where each node denotes a cluster of amino acids. The nodes are labeled with an evolutionary profile derived from the multiple alignment of homologous sequences. Then, a shortest-path graph kernel is used to calculate similarities between the graphs. Finally, a support vector machine using this graph kernel is used to train classifiers for protein function prediction. We applied the proposed method to two separate problems, namely, prediction of enzymes and prediction of DNA-binding proteins. In both cases, the results showed that the proposed method outperformed other state-of-the-art methods.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► A protein structure is represented using a graph by clustering amino acids into spatial groups. ► A graph kernel method is used to compare graph. ► The graph kernel is embedded into support vector machine to predict protein functions with improved performance.

Keywords
Protein function prediction; Graph kernel; Support vector machine
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A new protein graph model for function prediction
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 37, April 2012, Pages 6–10
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us