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Results: 1 to 20 of 96

Related Citations for PubMed (Select 17332022)


NucPred--predicting nuclear localization of proteins.

Brameier M, Krings A, MacCallum RM.

Bioinformatics. 2007 May 1;23(9):1159-60. Epub 2007 Mar 1.


Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms.

Chou KC, Shen HB.

Nat Protoc. 2008;3(2):153-62. doi: 10.1038/nprot.2007.494.


Prediction of nuclear proteins using nuclear translocation signals proposed by probabilistic latent semantic indexing.

Su EC, Chang JM, Cheng CW, Sung TY, Hsu WL.

BMC Bioinformatics. 2012;13 Suppl 17:S13. doi: 10.1186/1471-2105-13-S17-S13. Epub 2012 Dec 13.


Hum-PLoc: a novel ensemble classifier for predicting human protein subcellular localization.

Chou KC, Shen HB.

Biochem Biophys Res Commun. 2006 Aug 18;347(1):150-7. Epub 2006 Jun 21. Erratum in: Biochem Biophys Res Commun. 2006 Oct 6;348(4):1479.


Predicting protein subnuclear location with optimized evidence-theoretic K-nearest classifier and pseudo amino acid composition.

Shen HB, Chou KC.

Biochem Biophys Res Commun. 2005 Nov 25;337(3):752-6. Epub 2005 Sep 28.


SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition.

Melvin I, Ie E, Kuang R, Weston J, Stafford WN, Leslie C.

BMC Bioinformatics. 2007 May 22;8 Suppl 4:S2.


ProClust: improved clustering of protein sequences with an extended graph-based approach.

Pipenbacher P, Schliep A, Schneckener S, Schönhuth A, Schomburg D, Schrader R.

Bioinformatics. 2002;18 Suppl 2:S182-91.


Protein sub-nuclear localization prediction using SVM and Pfam domain information.

Kumar R, Jain S, Kumari B, Kumar M.

PLoS One. 2014 Jun 4;9(6):e98345. doi: 10.1371/journal.pone.0098345. eCollection 2014.


The 3of5 web application for complex and comprehensive pattern matching in protein sequences.

Seiler M, Mehrle A, Poustka A, Wiemann S.

BMC Bioinformatics. 2006 Mar 16;7:144.


BaCelLo: a balanced subcellular localization predictor.

Pierleoni A, Martelli PL, Fariselli P, Casadio R.

Bioinformatics. 2006 Jul 15;22(14):e408-16.


WebAllergen: a web server for predicting allergenic proteins.

Riaz T, Hor HL, Krishnan A, Tang F, Li KB.

Bioinformatics. 2005 May 15;21(10):2570-1. Epub 2005 Mar 3.


pTARGET [corrected] a new method for predicting protein subcellular localization in eukaryotes.

Guda C, Subramaniam S.

Bioinformatics. 2005 Nov 1;21(21):3963-9. Epub 2005 Sep 6. Erratum in: Bioinformatics. 2005 Dec 15;21(24):4434.


An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences.

Ye K, Kosters WA, Ijzerman AP.

Bioinformatics. 2007 Mar 15;23(6):687-93. Epub 2007 Jan 19.


PCI-SS: MISO dynamic nonlinear protein secondary structure prediction.

Green JR, Korenberg MJ, Aboul-Magd MO.

BMC Bioinformatics. 2009 Jul 17;10:222. doi: 10.1186/1471-2105-10-222.


Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure.

Song J, Yuan Z, Tan H, Huber T, Burrage K.

Bioinformatics. 2007 Dec 1;23(23):3147-54. Epub 2007 Oct 17.


Detection of alpha-rod protein repeats using a neural network and application to huntingtin.

Palidwor GA, Shcherbinin S, Huska MR, Rasko T, Stelzl U, Arumughan A, Foulle R, Porras P, Sanchez-Pulido L, Wanker EE, Andrade-Navarro MA.

PLoS Comput Biol. 2009 Mar;5(3):e1000304. doi: 10.1371/journal.pcbi.1000304. Epub 2009 Mar 13.


CASVM: web server for SVM-based prediction of caspase substrates cleavage sites.

Wee LJ, Tan TW, Ranganathan S.

Bioinformatics. 2007 Dec 1;23(23):3241-3. Epub 2007 Jun 28.


MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition.

Höglund A, Dönnes P, Blum T, Adolph HW, Kohlbacher O.

Bioinformatics. 2006 May 15;22(10):1158-65. Epub 2006 Jan 20.


Predicting protein structure classes from function predictions.

Sommer I, Rahnenführer J, Domingues FS, de Lichtenberg U, Lengauer T.

Bioinformatics. 2004 Mar 22;20(5):770-6. Epub 2004 Jan 29.

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