Anil Korkut
Associate Professor
The University of Texas MD Anderson Cancer Center
Department of Bioinformatics & Computational Biology
The Korkut laboratory uses a basic science approach to have a major impact on cancer care. Dr. Korkut is an expert in computational biology, network pharmacology and cancer systems biology. His research interests span a wide range of major problems in cancer biology such as resistance to targeted agents in various cancers (e.g., BRAF and NRAS mutated melanoma, HER2+ breast cancer), resistance to immunotherapy, and genomics guided design of rational combination therapies. Korkut lab uses a set of experimental and computational biology tools to study resistance mechanisms and develop rational combination therapies. His laboratory also works on development of network inference and machine learning algorithms to analyze high-throughput cancer omics data. Trainees in the Korkut lab will engage in design and execution of high-throughput drug response profiling experiments, network modeling of drug response/resistance mechanisms and in silico discovery of combination therapies. Dr. Korkut joined MDACC from Memorial Sloan Kettering Cancer Center (MSKCC). At MSKCC, he developed and used systems biology methods to predict responses to targeted perturbations in cancer cells. In particular, he developed quantitative network pharmacology methods, which combine systematic perturbation experiments, phospho-proteomic profiling and network inference algorithms. Dr. Korkut published numerous papers in journals such as PNAS, Cell, eLife, Cell Ssytems and holds two patents for identifying drug combinations for reduced drug resistance in cancer treatment. He completed his PhD in the Biochemistry and Molecular Biophysics department at Columbia University (NY). His PhD thesis was on development and application of algorithms to calculate large-scale conformational transition pathways of macromolecules.
Education & Training
Ph.D. - Columbia University - 2009