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Updated: Dec 30, 2025

Preparation of Chloroplast Sub-compartments from Arabidopsis for the Analysis of Protein Localization by Immunoblotting or Proteomics
Published on: October 19, 2018
An Overview on Predicting Protein Subchloroplast Localization by using Machine Learning Methods
Meng-Lu Liu1, Wei Su1, Zheng-Xing Guan1
1Key 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.
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.
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