Modelling cancer progression using Mutual Hazard Networks

Abstract excerpt

<h4>Motivation</h4> Cancer progresses by accumulating genomic events, such as mutations and copy number alterations, whose chronological order is key to understanding the disease but difficult to observe. Instead, cancer progression models use co-occurence patterns in cross-sectional data to infer epistatic interactions between events and thereby uncover their most likely order of occurence. State-of-the-art prog...

Topics

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• Algorithms
• Bioinformatics and Genomic Networks
• Cancer Genomics and Diagnostics
• Genetic factors in colorectal cancer
• Genomics
• Models, Theoretical
• Mutation
• Neoplasms

Identifiers and source

Literature Corpus work

3387af47-8a29-5b6f-b559-d7b5e1f6fb3e

DOI

10.1101/450841