PSORTb v.2.0: Expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysis | Zendy

Jennifer L. Gardy | Zendy; Matthew R. Laird | Zendy; FenLing Chen | Zendy; Sébastien Rey | Zendy; Calum J. Walsh | Zendy; Martin Ester | Zendy; Fiona S. L. Brinkman | Zendy

Open Access

PSORTb v.2.0: Expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysis

Author(s) -

Jennifer L. Gardy,

Matthew R. Laird,

FenLing Chen,

Sébastien Rey,

Calum J. Walsh,

Martin Ester,

Fiona S. L. Brinkman

Publication year - 2004

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bti057

Subject(s) - proteome , computer science , n gram , subsequence , support vector machine , computational biology , mit license , subcellular localization , biology , artificial intelligence , software , bioinformatics , genetics , mathematics , programming language , language model , mathematical analysis , bounded function , cytoplasm

PSORTb v.1.1 is the most precise bacterial localization prediction tool available. However, the program's predictive coverage and recall are low and the method is only applicable to Gram-negative bacteria. The goals of the present work are as follows: increase PSORTb's coverage while maintaining the existing precision level, expand it to include Gram-positive bacteria and then carry out a comparative analysis of localization.

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