Inferring time-aware models of cancer progression using Timed Hazard Networks

Abstract excerpt

Analysis of the sequential accumulation of genetic events, such as mutations and copy number alterations, is key to understanding disease dynamics and may provide insights into the design of targeted therapies. Oncogenetic graphical models are computational methods that use genetic event profiles from cross-sectional genomic data to infer the statistical dependencies between events and thereby deduce their tempora...

Topics

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• Algorithms
• Cancer Genomics and Diagnostics
• Child
• Cross-Sectional Studies
• Genetic factors in colorectal cancer
• Glioblastoma
• Mutation
• Neoplasms

Identifiers and source

Literature Corpus work

59e9e784-6785-56e5-aadd-a0f0f9b359e4

DOI

10.1101/2022.10.23.513436