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Similar articles for PubMed (Select 23758891)

1.

Utilizing protein structure to identify non-random somatic mutations.

Ryslik GA, Cheng Y, Cheung KH, Modis Y, Zhao H.

BMC Bioinformatics. 2013 Jun 13;14:190. doi: 10.1186/1471-2105-14-190.

2.

A graph theoretic approach to utilizing protein structure to identify non-random somatic mutations.

Ryslik GA, Cheng Y, Cheung KH, Modis Y, Zhao H.

BMC Bioinformatics. 2014 Mar 26;15:86. doi: 10.1186/1471-2105-15-86.

3.

A spatial simulation approach to account for protein structure when identifying non-random somatic mutations.

Ryslik GA, Cheng Y, Cheung KH, Bjornson RD, Zelterman D, Modis Y, Zhao H.

BMC Bioinformatics. 2014 Jul 3;15:231. doi: 10.1186/1471-2105-15-231.

4.

Statistical method on nonrandom clustering with application to somatic mutations in cancer.

Ye J, Pavlicek A, Lunney EA, Rejto PA, Teng CH.

BMC Bioinformatics. 2010 Jan 7;11:11. doi: 10.1186/1471-2105-11-11.

5.

Multiplicity: an organizing principle for cancers and somatic mutations.

Frey LJ, Piccolo SR, Edgerton ME.

BMC Med Genomics. 2011 Jun 29;4:52. doi: 10.1186/1755-8794-4-52.

6.

OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes.

Tamborero D, Gonzalez-Perez A, Lopez-Bigas N.

Bioinformatics. 2013 Sep 15;29(18):2238-44. doi: 10.1093/bioinformatics/btt395. Epub 2013 Jul 24.

7.

Inferring the functional effects of mutation through clusters of mutations in homologous proteins.

Yue P, Forrest WF, Kaminker JS, Lohr S, Zhang Z, Cavet G.

Hum Mutat. 2010 Mar;31(3):264-71. doi: 10.1002/humu.21194.

PMID:
20052764
8.

Detecting clusters of mutations.

Zhou T, Enyeart PJ, Wilke CO.

PLoS One. 2008;3(11):e3765. doi: 10.1371/journal.pone.0003765. Epub 2008 Nov 19.

9.

SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering.

Van den Eynden J, Fierro AC, Verbeke LP, Marchal K.

BMC Bioinformatics. 2015 Apr 23;16(1):125. [Epub ahead of print]

10.

Bayesian hierarchical clustering for microarray time series data with replicates and outlier measurements.

Cooke EJ, Savage RS, Kirk PD, Darkins R, Wild DL.

BMC Bioinformatics. 2011 Oct 13;12:399. doi: 10.1186/1471-2105-12-399.

11.

PFClust: a novel parameter free clustering algorithm.

Mavridis L, Nath N, Mitchell JB.

BMC Bioinformatics. 2013 Jul 3;14:213. doi: 10.1186/1471-2105-14-213.

12.

Structural and functional impact of cancer-related missense somatic mutations.

Shi Z, Moult J.

J Mol Biol. 2011 Oct 21;413(2):495-512. doi: 10.1016/j.jmb.2011.06.046. Epub 2011 Jul 13.

13.

A hybrid clustering of protein binding sites.

Iván G, Szabadka Z, Grolmusz V.

FEBS J. 2010 Mar;277(6):1494-502. doi: 10.1111/j.1742-4658.2010.07578.x. Epub 2010 Feb 10.

PMID:
20148971
14.

Simultaneous identification of multiple driver pathways in cancer.

Leiserson MD, Blokh D, Sharan R, Raphael BJ.

PLoS Comput Biol. 2013;9(5):e1003054. doi: 10.1371/journal.pcbi.1003054. Epub 2013 May 23.

15.

Incorporating molecular and functional context into the analysis and prioritization of human variants associated with cancer.

Peterson TA, Nehrt NL, Park D, Kann MG.

J Am Med Inform Assoc. 2012 Mar-Apr;19(2):275-83. doi: 10.1136/amiajnl-2011-000655.

16.

Mutational analysis of EGFR and related signaling pathway genes in lung adenocarcinomas identifies a novel somatic kinase domain mutation in FGFR4.

Marks JL, McLellan MD, Zakowski MF, Lash AE, Kasai Y, Broderick S, Sarkaria IS, Pham D, Singh B, Miner TL, Fewell GA, Fulton LL, Mardis ER, Wilson RK, Kris MG, Rusch VW, Varmus H, Pao W.

PLoS One. 2007 May 9;2(5):e426.

17.

Sequence and structure signatures of cancer mutation hotspots in protein kinases.

Dixit A, Yi L, Gowthaman R, Torkamani A, Schork NJ, Verkhivker GM.

PLoS One. 2009 Oct 16;4(10):e7485. doi: 10.1371/journal.pone.0007485.

18.

Combining Pareto-optimal clusters using supervised learning for identifying co-expressed genes.

Maulik U, Mukhopadhyay A, Bandyopadhyay S.

BMC Bioinformatics. 2009 Jan 20;10:27. doi: 10.1186/1471-2105-10-27.

20.
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