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Modelling cancer progression using Mutual Hazard Networks

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


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-occurrence patterns in cross-sectional data to infer epistatic interactions between events and thereby uncover their most likely order of occurrence. ...


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