• 1) Introduction
• 2) ePSORTdb
• 3) cPSORTdb
• 4) Using PSORTdb
• 5) ePSORTdb Fields
• 6) cPSORTdb Fields

Introduction

Identification of a bacterial protein’s SCL provides valuable clues regarding its biological function. For example, surface exposed or secreted proteins are of primary interest due to their potential as vaccine candidates, diagnostic agents (environmental or medical) and the ease with which they may be accessible to drugs. Computational SCL analysis of the growing number of completed bacterial genomes or individual proteins allows researchers to screen for vaccine/drug candidates, automatically annotate gene products or select proteins for further study.

PSORTdb is a database of SCL for bacteria that contains both information determined through laboratory experimentation (ePSORTdb dataset) and computational predictions (cPSORTdb dataset). The dataset of experimentally verified information (>11000 proteins) was manually curated by us and represents the largest dataset of its kind. The second component of this database contains computational analyses of proteins deduced from the most recent NCBI dataset of completely sequenced genomes. Analyses are currently calculated using PSORTb, the most precise automated SCL predictor for bacterial proteins.

PSORTdb database belongs to PSORT family which provides resources and links for subcellular localization prediction.

The manuscript for the new version of PSORTdb is currently under preparation. In the mean time, if you use PSORTdb in your research, we would greatly appreciate if you cited one of the following publications:

If you use PSORTdb in your research, we would greatly appreciate if you cited the following publication:

Yu, N.Y., Laird, M.R., Spencer, C, and Brinkman, F.S.L. (2011) PSORTdb--an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea. Nucleic Acids Research. 39:D241-244.

PSORTdb: Rey, S., M. Acab, J.L. Gardy, M.R. Laird, K. deFays, C. Lambert, and F.S.L. Brinkman (2005). PSORTdb: A Database of Subcellular Localizations for Bacteria. Nucleic Acids Research. 33:D164-168. (Database issue)