Every which way? On predicting tumor evolution using cancer progression models

Successful prediction of the likely paths of tumor progression is valuable for diagnostic, prognostic, and treatment purposes. Cancer progression models (CPMs) use cross-sectional samples to identify restrictions in the order of accumulation of driver mutations and thus CPMs encode the paths of tumo...

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Veröffentlicht in:	PLoS computational biology 2019-08, Vol.15 (8), p.e1007246-e1007246
Hauptverfasser:	Diaz-Uriarte, Ramon, Vasallo, Claudia
Format:	Artikel
Sprache:	eng
Schlagworte:	Acquisitions & mergers Analysis Bayes Theorem Biochemistry Biology Biology and Life Sciences Cancer Chromosomes Computational Biology Computer and Information Sciences Computer Simulation Cross-Sectional Studies Data modeling software Databases, Factual Datasets Development and progression Diagnostic systems Disease Progression Evolution Evolution & development Evolution, Molecular Fitness Fitness (Genetics) Genes Genetic aspects Genetic Fitness Genomes Genomics Genotype Genotype & phenotype Humans Models, Biological Models, Genetic Mutation Neoplasms - genetics Neoplasms - pathology Neoplastic Processes Predictions Prognosis Reproductive fitness Research and Analysis Methods Restrictions Tumors Upper bounds
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