A simplicial complex-based approach to unmixing tumor progression data-Reference-Cited by-同舟云学术

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A simplicial complex-based approach to unmixing tumor progression data

Published:2015-08-12 Issue:1 Volume:16 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Roman Theodore,Nayyeri Amir,Fasy Brittany Terese,Schwartz Russell

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/article/10.1186/s12859-015-0694-x/fulltext.html

Reference90 articles.

1. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011; 144(5):646–74.

2. Desper R, Jiang F, Kallioniemi OP, Moch H, Papadimitriou CH, Schäffer AA. Inferring tree models for oncogenesis from comparative genome hybridization data. J Comput Biol. 1999; 6:37–51.

3. Pennington G, Smith CA, Shackney S, Schwartz R. Reconstructing tumor phylogenies from heterogeneous single-cell data. J Bioinforma Comput Biol. 2007; 5(02a):407–27.

4. Pennington G, Smith C, Shackney S, Schwartz R. Expectation-maximization method for reconstructing tumor phylogenies from single-cell data. In: Computational Systems Bioinformatics Conference (CSB): 2006. p. 371–80.

5. Navin N, Krasnitz A, Rodgers L, Cook K, Meth J, Kendall J, et al. Inferring tumor progression from genomic heterogeneity. Genome Res. 2010; 20(1):68–80.

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