07/24/2017 @ 13:30-14:15
Research Talk by Fabio Vandin
Computational methods for survival analysis in genome-wide cancer studies 
1. Vandin, F., Upfal, E. and Raphael, B.J., 2011. Algorithms for detecting significantly mutated pathways in cancer. Journal of Computational Biology, 18(3), pp.507-522.
2. Raphael, B.J., Dobson, J.R., Oesper, L. and Vandin, F., 2014. Identifying driver mutations in sequenced cancer genomes: computational approaches to enable precision medicine. Genome medicine, 6(1), p.5.
3. Leiserson, M.D., Vandin, F., Wu, H.T., Dobson, J.R., Eldridge, J.V., Thomas, J.L., Papoutsaki, A., Kim, Y., Niu, B., McLellan, M. and Lawrence, M.S., 2015. Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nature genetics, 47(2), pp.106-114.
4. Vandin, F., Papoutsaki, A., Raphael, B.J. and Upfal, E., 2015. Accurate computation of survival statistics in genome-wide studies. PLoS Comput Biol, 11(5), p.e1004071.
5. Hansen, T. and Vandin, F., 2016. Finding Mutated Subnetworks Associated with Survival in Cancer. arXiv preprint arXiv:1604.02467.
Fabio Vandin | Computational methods for survival analysis in genome-wide cancer studies | CGSI 2017