title: Computing tumor trees from single cells.
abstract: Computational methods have been developed to reconstruct evolutionary lineages from tumors using single-cell genomic data. The resulting tumor trees have important applications in cancer research and clinical oncology.Please see related Research articles: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0929-9 and http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0936-x .
authors.affiliation: Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.|Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Davis
authors.affiliation: Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. nnavin@mdanderson.org.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. nnavin@mdanderson.org.
authors.forename: Nicholas E
authors.initials: NE
authors.lastname: Navin
mesh_terms: D002471:Cell Transformation, Neoplastic / Q000235:genetics; D060965:Clonal Evolution / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D018740:Genetic Heterogeneity; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008390:Markov Chains; D009010:Monte Carlo Method; D009154:Mutation; D009369:Neoplasms / Q000175:diagnosis / Q000235:genetics*; D010802:Phylogeny; D059010:Single-Cell Analysis / Q000379:methods