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Current Protein & Peptide Science

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ISSN (Print): 1389-2037
ISSN (Online): 1875-5550

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General Review Article

An Overview on Predicting Protein Subchloroplast Localization by using Machine Learning Methods

Author(s): Meng-Lu Liu , Wei Su , Zheng-Xing Guan , Dan Zhang , Wei Chen *, Li Liu * and Hui Ding *

Volume 21, Issue 12, 2020

Page: [1229 - 1241] Pages: 13

DOI: 10.2174/1389203721666200117153412

Price: $65

Abstract

The chloroplast is a type of subcellular organelle of green plants and eukaryotic algae, which plays an important role in the photosynthesis process. Since the function of a protein correlates with its location, knowing its subchloroplast localization is helpful for elucidating its functions. However, due to a large number of chloroplast proteins, it is costly and time-consuming to design biological experiments to recognize subchloroplast localizations of these proteins. To address this problem, during the past ten years, twelve computational prediction methods have been developed to predict protein subchloroplast localization. This review summarizes the research progress in this area. We hope the review could provide important guide for further computational study on protein subchloroplast localization.

Keywords: Protein, subchloroplast localization, machine learning method, protein sequence properties, feature selection, dataset.

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