Publication: Quantifying cancer progression with conjunctive Bayesian networks
Quantifying cancer progression with conjunctive Bayesian networks
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Gerstung, M., Baudis, M., Moch, H., & Beerenwinkel, N. (2009). Quantifying cancer progression with conjunctive Bayesian networks. Bioinformatics, 25(21), 2809–2815. https://doi.org/10.1093/bioinformatics/btp505
Abstract
Abstract
Abstract
MOTIVATION: Cancer is an evolutionary process characterized by accumulating mutations. However, the precise timing and the order of genetic alterations that drive tumor progression remain enigmatic. RESULTS: We present a specific probabilistic graphical model for the accumulation of mutations and their interdependencies. The Bayesian network models cancer progression by an explicit unobservable accumulation process in time that is separated from the observable but error-prone detection of mutations. Model parameters are estimated by a
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- Gerstung, M
- Moch, H
- Beerenwinkel, N
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Gerstung, M., Baudis, M., Moch, H., & Beerenwinkel, N. (2009). Quantifying cancer progression with conjunctive Bayesian networks. Bioinformatics, 25(21), 2809–2815. https://doi.org/10.1093/bioinformatics/btp505
