Evidence map›Paper›PMID 16689702›Full record

ArticleGenomics, proteomics & bioinformatics2006

PredSL: a tool for the N-terminal sequence-based prediction of protein subcellular localization.

Evangelia I Petsalaki, Pantelis G Bagos, Zoi I Litou, Stavros J Hamodrakas

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Article in Genomics, proteomics & bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.

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82citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

82 citing papers in PubMed.

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  9. Protein subcellular localization prediction tools.Computational and structural biotechnology journal · 2024
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  12. Pyrenoid proteomics reveals independent evolution of the COProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. Article
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  18. Review
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22 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Evangelia I PetsalakiDepartment of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 15701, Greece.
Pantelis G Bagos
Zoi I Litou
Stavros J Hamodrakas

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to predict the subcellular localization of a protein from its sequence is of great importance, as it provides information about the protein's function. We present a computational tool, PredSL, which utilizes neural networks, Markov chains, profile hidden Markov models, and scoring matrices for the prediction of the subcellular localization of proteins in eukaryotic cells from the N-terminal amino acid sequence. It aims to classify proteins into five groups: chloroplast, thylakoid, mitochondrion, secretory pathway, and "other". When tested in a five-fold cross-validation procedure, PredSL demonstrates 86.7% and 87.1% overall accuracy for the plant and non-plant datasets, respectively. Compared with TargetP, which is the most widely used method to date, and LumenP, the results of PredSL are comparable in most cases. When tested on the experimentally verified proteins of the Saccharomyces cerevisiae genome, PredSL performs comparably if not better than any available algorithm for the same task. Furthermore, PredSL is the only method capable for the prediction of these subcellular localizations that is available as a stand-alone application through the URL:http://bioinformatics.biol.uoa.gr/PredSL/.

Indexed as

Protein Sorting SignalsSoftwareAlgorithmsComputational BiologyDatabases, ProteinOrganellesPeptide FragmentsProteinsSequence Analysis, ProteinPeptide FragmentsProteinsProtein Sorting Signals

Identifiers

PMID16689702
PMCPMC5054032

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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.