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ludc webb

Jiangming Sun

Bioinformatician

ludc webb

PlantLoc: an accurate web server for predicting plant protein subcellular localization by substantiality motif.

Author

  • Shengnan Tang
  • Tonghua Li
  • Peisheng Cong
  • Wenwei Xiong
  • Zhiheng Wang
  • Jiangming Sun

Summary, in English

Knowledge of subcellular localizations (SCLs) of plant proteins relates to their functions and aids in understanding the regulation of biological processes at the cellular level. We present PlantLoc, a highly accurate and fast webserver for predicting the multi-label SCLs of plant proteins. The PlantLoc server has two innovative characters: building localization motif libraries by a recursive method without alignment and Gene Ontology information; and establishing simple architecture for rapidly and accurately identifying plant protein SCLs without a machine learning algorithm. PlantLoc provides predicted SCLs results, confidence estimates and which is the substantiality motif and where it is located on the sequence. PlantLoc achieved the highest accuracy (overall accuracy of 80.8%) of identification of plant protein SCLs as benchmarked by using a new test dataset compared other plant SCL prediction webservers. The ability of PlantLoc to predict multiple sites was also significantly higher than for any other webserver. The predicted substantiality motifs of queries also have great potential for analysis of relationships with protein functional regions. The PlantLoc server is available at http://cal.tongji.edu.cn/PlantLoc/.

Department/s

  • Diabetes - Molecular Metabolism

Publishing year

2013

Language

English

Pages

441-447

Publication/Series

Nucleic Acids Research

Volume

41

Issue

W1

Document type

Journal article

Publisher

Oxford University Press

Topic

  • Endocrinology and Diabetes

Status

Published

Research group

  • Diabetes - Molecular Metabolism

ISBN/ISSN/Other

  • ISSN: 1362-4962