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Items: 1 to 20 of 175

1.

Combining machine learning and homology-based approaches to accurately predict subcellular localization in Arabidopsis.

Kaundal R, Saini R, Zhao PX.

Plant Physiol. 2010 Sep;154(1):36-54. doi: 10.1104/pp.110.156851. Epub 2010 Jul 20.

2.
3.

Identification of novel plant peroxisomal targeting signals by a combination of machine learning methods and in vivo subcellular targeting analyses.

Lingner T, Kataya AR, Antonicelli GE, Benichou A, Nilssen K, Chen XY, Siemsen T, Morgenstern B, Meinicke P, Reumann S.

Plant Cell. 2011 Apr;23(4):1556-72. doi: 10.1105/tpc.111.084095. Epub 2011 Apr 12.

4.

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.

PMID:
16808903
5.

Sorting signals, N-terminal modifications and abundance of the chloroplast proteome.

Zybailov B, Rutschow H, Friso G, Rudella A, Emanuelsson O, Sun Q, van Wijk KJ.

PLoS One. 2008 Apr 23;3(4):e1994. doi: 10.1371/journal.pone.0001994.

6.

Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis.

Narsai R, Devenish J, Castleden I, Narsai K, Xu L, Shou H, Whelan J.

Plant J. 2013 Dec;76(6):1057-73. doi: 10.1111/tpj.12357. Epub 2013 Nov 29.

7.

PRIN: a predicted rice interactome network.

Gu H, Zhu P, Jiao Y, Meng Y, Chen M.

BMC Bioinformatics. 2011 May 16;12:161. doi: 10.1186/1471-2105-12-161.

8.

Mimicking cellular sorting improves prediction of subcellular localization.

Nair R, Rost B.

J Mol Biol. 2005 Apr 22;348(1):85-100.

PMID:
15808855
9.

Prediction of protein subcellular locations using fuzzy k-NN method.

Huang Y, Li Y.

Bioinformatics. 2004 Jan 1;20(1):21-8.

PMID:
14693804
10.
11.

MSLoc-DT: a new method for predicting the protein subcellular location of multispecies based on decision templates.

Zhang SW, Liu YF, Yu Y, Zhang TH, Fan XN.

Anal Biochem. 2014 Mar 15;449:164-71. doi: 10.1016/j.ab.2013.12.013. Epub 2013 Dec 21.

PMID:
24361712
12.

SUBAcon: a consensus algorithm for unifying the subcellular localization data of the Arabidopsis proteome.

Hooper CM, Tanz SK, Castleden IR, Vacher MA, Small ID, Millar AH.

Bioinformatics. 2014 Dec 1;30(23):3356-64. doi: 10.1093/bioinformatics/btu550. Epub 2014 Aug 22.

PMID:
25150248
13.

eSLDB: eukaryotic subcellular localization database.

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

Nucleic Acids Res. 2007 Jan;35(Database issue):D208-12. Epub 2006 Nov 15.

14.

Structure-based comparative analysis and prediction of N-linked glycosylation sites in evolutionarily distant eukaryotes.

Lam PV, Goldman R, Karagiannis K, Narsule T, Simonyan V, Soika V, Mazumder R.

Genomics Proteomics Bioinformatics. 2013 Apr;11(2):96-104. doi: 10.1016/j.gpb.2012.11.003. Epub 2013 Feb 28.

15.

Combining experimental and predicted datasets for determination of the subcellular location of proteins in Arabidopsis.

Heazlewood JL, Tonti-Filippini J, Verboom RE, Millar AH.

Plant Physiol. 2005 Oct;139(2):598-609.

16.

Prediction of protein subcellular localization.

Yu CS, Chen YC, Lu CH, Hwang JK.

Proteins. 2006 Aug 15;64(3):643-51.

PMID:
16752418
17.

Validating subcellular localization prediction tools with mycobacterial proteins.

Restrepo-Montoya D, Vizcaíno C, Niño LF, Ocampo M, Patarroyo ME, Patarroyo MA.

BMC Bioinformatics. 2009 May 7;10:134. doi: 10.1186/1471-2105-10-134.

18.

ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization.

Huang WL, Tung CW, Ho SW, Hwang SF, Ho SY.

BMC Bioinformatics. 2008 Feb 1;9:80. doi: 10.1186/1471-2105-9-80.

20.

Gpos-PLoc: an ensemble classifier for predicting subcellular localization of Gram-positive bacterial proteins.

Shen HB, Chou KC.

Protein Eng Des Sel. 2007 Jan;20(1):39-46. Epub 2007 Jan 23.

PMID:
17244638

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