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Items: 1 to 20 of 110


Improving subcellular localization prediction using text classification and the gene ontology.

Fyshe A, Liu Y, Szafron D, Greiner R, Lu P.

Bioinformatics. 2008 Nov 1;24(21):2512-7. doi: 10.1093/bioinformatics/btn463. Epub 2008 Aug 26.


Gene ontology based transfer learning for protein subcellular localization.

Mei S, Fei W, Zhou S.

BMC Bioinformatics. 2011 Feb 2;12:44. doi: 10.1186/1471-2105-12-44.


Protein function prediction using text-based features extracted from the biomedical literature: the CAFA challenge.

Wong A, Shatkay H.

BMC Bioinformatics. 2013;14 Suppl 3:S14. doi: 10.1186/1471-2105-14-S3-S14. Epub 2013 Feb 28.


Automatic extraction of gene/protein biological functions from biomedical text.

Koike A, Niwa Y, Takagi T.

Bioinformatics. 2005 Apr 1;21(7):1227-36. Epub 2004 Oct 27.


mGOASVM: Multi-label protein subcellular localization based on gene ontology and support vector machines.

Wan S, Mak MW, Kung SY.

BMC Bioinformatics. 2012 Nov 6;13:290. doi: 10.1186/1471-2105-13-290.


Ranking Gene Ontology terms for predicting non-classical secretory proteins in eukaryotes and prokaryotes.

Huang WL.

J Theor Biol. 2012 Nov 7;312:105-13. doi: 10.1016/j.jtbi.2012.07.027. Epub 2012 Aug 8.


WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms.

Chi SM, Nam D.

Bioinformatics. 2012 Apr 1;28(7):1028-30. doi: 10.1093/bioinformatics/bts062. Epub 2012 Jan 31.


Extracting synonymous gene and protein terms from biological literature.

Yu H, Agichtein E.

Bioinformatics. 2003;19 Suppl 1:i340-9.


Semantically linking and browsing PubMed abstracts with gene ontology.

Vanteru BC, Shaik JS, Yeasin M.

BMC Genomics. 2008;9 Suppl 1:S10. doi: 10.1186/1471-2164-9-S1-S10.


GoPubMed: exploring PubMed with the Gene Ontology.

Doms A, Schroeder M.

Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W783-6.


GOASVM: a subcellular location predictor by incorporating term-frequency gene ontology into the general form of Chou's pseudo-amino acid composition.

Wan S, Mak MW, Kung SY.

J Theor Biol. 2013 Apr 21;323:40-8. doi: 10.1016/j.jtbi.2013.01.012. Epub 2013 Jan 29.


HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

Wan S, Mak MW, Kung SY.

PLoS One. 2014 Mar 19;9(3):e89545. doi: 10.1371/journal.pone.0089545. eCollection 2014.


MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction.

Blum T, Briesemeister S, Kohlbacher O.

BMC Bioinformatics. 2009 Sep 1;10:274. doi: 10.1186/1471-2105-10-274.


AliBaba: PubMed as a graph.

Plake C, Schiemann T, Pankalla M, Hakenberg J, Leser U.

Bioinformatics. 2006 Oct 1;22(19):2444-5. Epub 2006 Jul 26.


Large-scale protein annotation through gene ontology.

Xie H, Wasserman A, Levine Z, Novik A, Grebinskiy V, Shoshan A, Mintz L.

Genome Res. 2002 May;12(5):785-94.


A method to improve protein subcellular localization prediction by integrating various biological data sources.

Tung TQ, Lee D.

BMC Bioinformatics. 2009 Jan 30;10 Suppl 1:S43. doi: 10.1186/1471-2105-10-S1-S43.


Supervised learning method for the prediction of subcellular localization of proteins using amino acid and amino acid pair composition.

Habib T, Zhang C, Yang JY, Yang MQ, Deng Y.

BMC Genomics. 2008;9 Suppl 1:S16. doi: 10.1186/1471-2164-9-S1-S16.

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