The overall goal of the work in the Sander lab is to solve biological problems using quantitative methods from bioinformatics, statistical physics, data sciences, statistics, computer science, and mathematics. We apply these computational methods to build predictive network models of molecular and cell-cell interactions, to support cancer precision medicine, and to make discoveries in structural and evolutionary biology.
Sander is an internationally recognized expert in computational and systems biology, cancer biology, and structural biology. He has extensive experience in cancer genomics, is a leader in The Cancer Genome Atlas (TCGA) project, and his group created the cBioPortal for Cancer Genomics. Sander’s laboratory has developed quantitative computational network models of cancer cells, which are predictive of drug response. His group has developed algorithms for pathway analysis and the design of combination therapies, with translational collaborations in melanoma, sarcoma, glioblastoma, kidney cancer, and prostate cancer.
His current research includes: (1) deriving quantitatively predictive network models from high-throughput molecular profiling; (2) discovering molecular processes responsible for oncogenesis and response to therapy across different cancer types; (3) rendering human biological knowledge computable and accessible, as an aid to biomedical discovery (cBioPortal, Pathway Commons); and (4) using evolutionary constraints derived from rich sequence information to predict previously unknown 3D structures of proteins and RNAs and to identify functional sites on both known and unknown structures.