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Items: 8

1.

Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data.

Ding J, Bashashati A, Roth A, Oloumi A, Tse K, Zeng T, Haffari G, Hirst M, Marra MA, Condon A, Aparicio S, Shah SP.

Bioinformatics. 2012 Jan 15;28(2):167-75. doi: 10.1093/bioinformatics/btr629. Epub 2011 Nov 13.

2.

Identifying driver mutations from sequencing data of heterogeneous tumors in the era of personalized genome sequencing.

Zhang J, Liu J, Sun J, Chen C, Foltz G, Lin B.

Brief Bioinform. 2014 Mar;15(2):244-55. doi: 10.1093/bib/bbt042. Epub 2013 Jul 1. Review.

PMID:
23818492
3.

Review of alignment and SNP calling algorithms for next-generation sequencing data.

Mielczarek M, Szyda J.

J Appl Genet. 2016 Feb;57(1):71-9. doi: 10.1007/s13353-015-0292-7. Epub 2015 Jun 9. Review.

PMID:
26055432
4.

Research and clinical applications of cancer genome sequencing.

Ku CS, Cooper DN, Ziogas DE, Halkia E, Tzaphlidou M, Roukos DH.

Curr Opin Obstet Gynecol. 2013 Feb;25(1):3-10. doi: 10.1097/GCO.0b013e32835af17c. Review.

PMID:
23108289
5.

Brief review of regression-based and machine learning methods in genetic epidemiology: the Genetic Analysis Workshop 17 experience.

Dasgupta A, Sun YV, K├Ânig IR, Bailey-Wilson JE, Malley JD.

Genet Epidemiol. 2011;35 Suppl 1:S5-11. doi: 10.1002/gepi.20642. Review.

6.

[The pathogenicity of somatic mutation to common tumors and developmental malformation of the nervous system].

Fang L, Xiaozhen S, Hua X, Xiaoli C.

Yi Chuan. 2016 Mar;38(3):196-205. doi: 10.16288/j.yczz.15-400. Review. Chinese.

PMID:
27001474
7.

Machine learning applications in genetics and genomics.

Libbrecht MW, Noble WS.

Nat Rev Genet. 2015 Jun;16(6):321-32. doi: 10.1038/nrg3920. Epub 2015 May 7. Review.

8.

Base changes in tumour DNA have the power to reveal the causes and evolution of cancer.

Hollstein M, Alexandrov LB, Wild CP, Ardin M, Zavadil J.

Oncogene. 2017 Jan 12;36(2):158-167. doi: 10.1038/onc.2016.192. Epub 2016 Jun 6. Review.

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