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

Journal: Current protein & peptide science
Published Date: Jan 1, 2020

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.

Authors

  • Meng-Lu Liu
    Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Wei Su
    Department of Science and Technology, Hebei Agricultural University, Huanghua, China.
  • Zheng-Xing Guan
    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 610054, China.
  • Dan Zhang
    School of Pharmacy, Southwest Medical University, Luzhou 646000, China.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.
  • Li Liu
    Metanotitia Inc., Shenzhen, China.
  • Hui Ding
    Medical School, Huanghe Science & Technology University, Zhengzhou 450063, PR China.

Keywords

External Resources

Popular Topics
Recent Journals