Machine Learning Predictions of Cancer Driver Mutations

E Joseph Jordan; Ravi Radhakrishnan

doi:10.1109/iarwisoci.2014.7034632

Machine Learning Predictions of Cancer Driver Mutations

Proc 2014 6th Int Adv Res Workshop In Silico Oncol Cancer Investig (2014). 2014 Nov:2014:10.1109/iarwisoci.2014.7034632. doi: 10.1109/iarwisoci.2014.7034632.

Authors

E Joseph Jordan¹, Ravi Radhakrishnan²

Affiliations

¹ The University of Pennsylvania Biochemistry and Molecular Biophysics Graduate Group, PA 19104 USA.
² The University of Pennsylvania Departments of Bioengineering, Chemical and Biomolecular Engineering, Biochemistry and Biophysics, PA 19104 USA.

Abstract

A method to predict the activation status of kinase domain mutations in cancer is presented. This method, which makes use of the machine learning technique support vector machines (SVM), has applications to cancer treatment, as well as numerous other diseases that involve kinase misregulation.

Abstract

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