Review of Protein Subcellular Localization Prediction

ISSN: 2212-392X (Online)
ISSN: 1574-8936 (Print)


Volume 9, 5 Issues, 2014


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Current Bioinformatics

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Alessandro Giuliani
Istituto Superiore di Sanitá (Italian NIH) Environment and Health Dept
Roma
Italy


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Review of Protein Subcellular Localization Prediction

Author(s): Zhen Wang, Quan Zou, Yi Jiang, Ying Ju and Xiangxiang Zeng

Affiliation: Department of Computer Science, Xiamen University, Xiamen 361005, China.

Abstract

Protein subcellular localization is closely related to protein functions. Protein can work only in specific subcellular positions, so protein localization in a cell is very important in studies on cytobiology, proteomics, and drug design. Protein subcellular localization prediction based on machine learning is timely and has generated great interest in the field of bioinformatics. This paper reviews the research status of this problem in recent years from the following four aspects: protein dataset construction, features extraction of protein sequence, machine learning algorithms, and web server construction. Finally, we analyzed the challenges in predicting protein subcellular localization and identified possible future research trends.

Keywords: Algorithm, features extraction, machine learning, protein subcellular localization.

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Article Details

Volume: 9
Issue Number: 3
First Page: 331
Last Page: 342
Page Count: 12
DOI: 10.2174/1574893609666140212000304
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