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Figure 1

From: Adaptively Weighted and Robust Mathematical Programming for the Discovery of Driver Gene Sets in Cancers

Figure 1

Overview of AWRMP. (a) We constructed binary-valued mutation matrices from mutation data files. (b) We used subsampling to make our method robust against the uncertainty and noise in the data. (c) The optimal gene set was evaluated based on coverage and exclusivity scores and annotated to analyse the gene interactions using DAVID. (d) We proposed a new mathematical programming model that uses adaptive weights to tune the balance between the coverage and mutual exclusivity.

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