3D-clustering algorithm for cancer driver gene detection
A new computational method developed in our lab, Oncodrive3D, has been published in Nucleic Acids Research.
The article, titled “Oncodrive3D: fast and accurate detection of structural clusters of somatic mutations under positive selection,” presents a new 3D-clustering algorithm for cancer driver gene detection. This method analyzes patterns of somatic mutations in cancer to identify protein regions that show a higher-than-expected frequency of mutations.
Oncodrive3D outperforms existing 3D-clustering methods and complements other driver detection approaches.
