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Recent Advance in Predicting Subcellular Localization of Mycobacterial Protein with Machine Learning Methods

Author(s):

Shi-Hao Li, Zheng-Xing Guan, Dan Zhang, Zi-Mei Zhang, Jian Huang, Wuritu Yang* and Hao Lin*  

Abstract:


Mycobacterium tuberculosis (MTB) can cause the terrible tuberculosis (TB), which is reported as one of the most dreadful epidemic. Although many biochemical molecular drugs have been developed to cope with this disease, the drug resistance—especially the multidrug-resistant (MDR) and extensively drug-resistance (XDR)—poses a huge threat to the treatment. However, traditional biochemical experimental method to tackle TB is time-consuming and costly. Benefited by the appearance of the enormous genomic and proteomic sequence data, TB can be treated via sequence-based biological computational approach-bioinformatics. Studies on predicting subcellular localization of mycobacterial protein (MBP) with high precision and efficiency may help figure out the biological function of these proteins and then provide useful insights for protein function annotation as well as drug design. In this review, we reported the progress that has been made in computational prediction of subcellular localization of MBP including the following aspects: 1) Benchmark datasets construction. 2) Feature extraction methods. 3) Feature selection techniques. 4) Application of several published prediction algorithms. 5) The published results. 6) The further study on prediction of subcellular localization of MBP.

Keywords:

subcellular localization, mycobacterial protein, support vector machine, feature selection

Affiliation:

Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu



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