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Title

 

 

 

 

SOSUI-GramN: high performance prediction for sub-cellular localization of proteins in Gram-negative bacteria

 

Authors

Kenichiro Imai1, 2, 3*, Naoyuki Asakawa1, Toshiyuki Tsuji1, Fumitsugu Akazawa1, Ayano Ino1, Masashi Sonoyama1 and Shigeki Mitaku1

 

Affiliation

1Department of Applied Physics, Graduate School of Engineering, Nagoya University, Furocho, Chikusa-ku, Nagoya 464-8606, Japan; 2 Toyota Physical and Chemical Research Institute, Nagakute-cho, Aichi 480-1192, Japan; 3 Present address: Computational Biology Research Center, AIST, Tokyo 135-0064, Japan

 

Email

imai@bp.nuap.nagoya-u.ac.jp; * Corresponding author

 

Article Type

Hypothesis

 

Date

received July 04, 2008; accepted July 06, 2008; published July 14, 2008

 

Abstract

A predictive software system, SOSUI-GramN, was developed for assessing the subcellular localization of proteins in Gram-negative bacteria. The system does not require the sequence homology data of any known sequences; instead, it uses only physicochemical parameters of the N- and C-terminal signal sequences, and the total sequence. The precision of the prediction system for subcellular localization to extracellular, outer membrane, periplasm, inner membrane and cytoplasmic medium was 92.3%, 89.4%, 86.4%, 97.5% and 93.5%, respectively, with corresponding recall rates of 70.3%, 87.5%, 76.0%, 97.5% and 88.4%, respectively. The overall performance for precision and recall obtained using this method was 92.9% and 86.7%, respectively. The comparison of performance of SOSUI-GramN with that of other methods showed the performance of prediction for extracellular proteins, as well as inner and outer membrane proteins, was either superior or equivalent to that obtained with other systems. SOSUI-GramN particularly improved the accuracy for predictions of extracellular proteins which is an area of weakness common to the other methods.

 

Keywords

subcellular localization of proteins; Gram-negative bacteria; physicochemical parameters; amino acids

 

Citation

Imai et al., Bioinformation 2(9): 417-421 (2008)

 

Edited by

P. Kangueane

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

Copyright

Publisher

 

Copyright Transfer Agreement

The authors of published articles in Bioinformation automatically transfer the copyright to the publisher upon formal acceptance. However, the authors reserve right to use the information contained in the article for non commercial purposes.

 

License

This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.