Title :
Algorithms and Genome Sequencing: Identifying Driver Pathways in Cancer
Author :
Vandin, Fabio ; Upfal, Eli ; Raphael, Benjamin J.
fDate :
3/1/2012 12:00:00 AM
Abstract :
Two proposed algorithms predict which combinations of mutations in cancer genomes are priorities for experimental study. One relies on interaction network data to identify recurrently mutated sets of genes, while the other searches for groups of mutations that exhibit specific combinatorial properties.
Keywords :
DNA; cancer; genetics; genomics; cancer genomes; driver pathways; genome sequencing; interaction network; Algorithm design and analysis; Bioinformatics; Cancer; Gene expression; Genomics; Markov processes; Molecular biomarkers; Monte Carlo methods; Prediction theory; Markov chain Monte Carlo; bioinformatics; cancer genomics; computational biology; diffusion processes; genome sequencing; networks;
