Modelling cancer progression using Mutual Hazard Networks

URN to cite this document:: urn:nbn:de:bvb:355-epub-400907
DOI to cite this document:: 10.5283/epub.40090

Schill, Rudolf ; Solbrig, Stefan ; Wettig, Tilo ; Spang, Rainer

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Date of publication of this fulltext: 26 Apr 2019 06:24

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Abstract

Motivation: 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. ...