4.3 Review

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

Journal

CURRENT PROTEIN & PEPTIDE SCIENCE
Volume 21, Issue 12, Pages 1229-1241

Publisher

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1389203721666200117153412

Keywords

Protein; subchloroplast localization; machine learning method; protein sequence properties; feature selection; dataset

Funding

  1. National Nature Scientific Foundation of China [61772119, 31771471, 61702430]
  2. Natural Science Foundation for Distinguished Young Scholars of Hebei Province [C2017209244]

Ask authors/readers for more resources

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. I low ever, 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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available