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The Scientific World Journal
Volume 2014, Article ID 542824, 9 pages
http://dx.doi.org/10.1155/2014/542824
Research Article

A Novel Method for Functional Annotation Prediction Based on Combination of Classification Methods

1Samsung Electronics, Suwon, Republic of Korea
2Department of Computer Science & Engineering, Gangneung-Wonju National University, Gangwon, Republic of Korea

Received 14 April 2014; Accepted 29 June 2014; Published 16 July 2014

Academic Editor: Young-Sik Jeong

Copyright © 2014 Jaehee Jung et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Automated protein function prediction defines the designation of functions of unknown protein functions by using computational methods. This technique is useful to automatically assign gene functional annotations for undefined sequences in next generation genome analysis (NGS). NGS is a popular research method since high-throughput technologies such as DNA sequencing and microarrays have created large sets of genes. These huge sequences have greatly increased the need for analysis. Previous research has been based on the similarities of sequences as this is strongly related to the functional homology. However, this study aimed to designate protein functions by automatically predicting the function of the genome by utilizing InterPro (IPR), which can represent the properties of the protein family and groups of the protein function. Moreover, we used gene ontology (GO), which is the controlled vocabulary used to comprehensively describe the protein function. To define the relationship between IPR and GO terms, three pattern recognition techniques have been employed under different conditions, such as feature selection and weighted value, instead of a binary one.