PSORTdb: a protein subcellular localization database for bacteria

被引:107
|
作者
Rey, S
Acab, M
Gardy, JL
Laird, MR
DeFays, K
Lambert, C
Brinkman, FSL
机构
[1] Fac Univ Notre Dame Paix, URBM, B-5000 Namur, Belgium
[2] Simon Fraser Univ, Dept Mol Biol & Biochem, Burnaby, BC V5A 1S6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
D O I
10.1093/nar/gki027
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Information about bacterial subcellular localization (SCL) is important for protein function prediction and identification of suitable drug/vaccine/diagnostic targets. PSORTdb (http://db.psort.org/) is a web-accessible database of SCL for bacteria that contains both information determined through laboratory experimentation and computational predictions. The dataset of experimentally verified information (similar to2000 proteins) was manually curated by us and represents the largest dataset of its kind. Earlier versions have been used for training SCL predictors, and its incorporation now into this new PSORTdb resource, with its associated additional annotation information and dataset version control, should aid researchers in future development of improved SCL predictors. 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. Both datasets can be accessed through the web using a very flexible text search engine, a data browser, or using BLAST, and the entire database or search results may be downloaded in various formats. Features such as GO ontologies and multiple accession numbers are incorporated to facilitate integration with other bioinformatics resources. PSORTdb is freely available under GNU General Public License.
引用
收藏
页码:D164 / D168
页数:5
相关论文
共 50 条
  • [1] PSORTdb: expanding the bacteria and archaea protein subcellular localization database to better reflect diversity in cell envelope structures
    Peabody, Michael A.
    Laird, Matthew R.
    Vlasschaert, Caitlyn
    Lo, Raymond
    Brinkman, Fiona S. L.
    NUCLEIC ACIDS RESEARCH, 2016, 44 (D1) : D663 - D668
  • [2] PSORTdb-an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea
    Yu, Nancy Y.
    Laird, Matthew R.
    Spencer, Cory
    Brinkman, Fiona S. L.
    NUCLEIC ACIDS RESEARCH, 2011, 39 : D241 - D244
  • [3] PSORTdb 4.0: expanded and redesigned bacterial and archaeal protein subcellular localization database incorporating new secondary localizations
    Lau, Wing Yin Venus
    Hoad, Gemma R.
    Jin, Vivian
    Winsor, Geoffrey L.
    Madyan, Ashmeet
    Gray, Kristen L.
    Laird, Matthew R.
    Lo, Raymond
    Brinkman, Fiona S. L.
    NUCLEIC ACIDS RESEARCH, 2021, 49 (D1) : D803 - D808
  • [4] Protein Subcellular Localization in Bacteria
    Rudner, David Z.
    Losick, Richard
    COLD SPRING HARBOR PERSPECTIVES IN BIOLOGY, 2010, 2 (04): : a000307
  • [5] DBSubLoc: database of protein subcellular localization
    Guo, T
    Hua, SJ
    Ji, XL
    Sun, ZR
    NUCLEIC ACIDS RESEARCH, 2004, 32 : D122 - D124
  • [6] LOCATE: a mammalian protein subcellular localization database
    Sprenger, Josefine
    Fink, J. Lynn
    Karunaratne, Seetha
    Hanson, Kelly
    Hamilton, Nicholas A.
    Teasdale, Rohan D.
    NUCLEIC ACIDS RESEARCH, 2008, 36 : D230 - D233
  • [7] LOCATE: a mouse protein subcellular localization database
    Fink, J. Lynn
    Aturaliya, Rajith N.
    Davis, Melissa J.
    Zhang, Fasheng
    Hanson, Kelly
    Teasdale, Melvena S.
    Kai, Chikatoshi
    Kawai, Jun
    Carninci, Piero
    Hayashizaki, Yoshihide
    Teasdale, Rohan D.
    NUCLEIC ACIDS RESEARCH, 2006, 34 : D213 - D217
  • [9] eSLDB: eukaryotic subcellular localization database
    Pierleoni, Andea
    Martelli, Pier Luigi
    Fariselli, Piero
    Casadio, Rita
    NUCLEIC ACIDS RESEARCH, 2007, 35 : D208 - D212
  • [10] Barcodes for subcellular protein localization
    Yizhe Zhang
    Alden Moss
    Kristine Tan
    Amy E. Herr
    Nature Biomedical Engineering, 2019, 3 : 673 - 675