Evidence map›Paper›PMID 20472543›Full record

ArticleBioinformatics (Oxford, England)2010

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

Nancy Y Yu, James R Wagner, Matthew R Laird, Gabor Melli, Sébastien Rey, Raymond Lo, Phuong Dao, S Cenk Sahinalp, Martin Ester, Leonard J Foster and 1 more

Abstract read
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Article in Bioinformatics (Oxford, England), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,368 papers.

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0cells of the map it votes in
1,368citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1,368 citing papers in PubMed.

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1,308 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

11 authors.

Nancy Y YuDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
James R Wagner
Matthew R Laird
Gabor Melli
Sébastien Rey
Raymond Lo
Phuong Dao
S Cenk Sahinalp
Martin Ester
Leonard J Foster
Fiona S L Brinkman

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

motivationPSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program.

resultsWe developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. AVAILABILITY: http://www.psort.org/psortb (download open source software or use the web interface). CONTACT: psort-mail@sfu.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

SoftwareArchaeaArchaeal ProteinsBacteriaBacterial ProteinsProteomicsSequence Analysis, ProteinArchaeal ProteinsBacterial Proteins

Identifiers

PMID20472543
PMCPMC2887053

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.