TY - JOUR AU - Daemen, Anneleen AU - Griffith, Obi L. AU - Heiser, Laura M. AU - Wang, Nicholas J. AU - Enache, Oana M. AU - Sanborn, Zachary AU - Pepin, Francois AU - Durinck, Steffen AU - Korkola, James E. AU - Griffith, Malachi AU - Hur, Joe S. AU - Huh, Nam AU - Chung, Jongsuk AU - Cope, Leslie AU - Fackler, Mary Jo AU - Umbricht, Christopher AU - Sukumar, Saraswati AU - Seth, Pankaj AU - Sukhatme, Vikas P. AU - Jakkula, Lakshmi R. AU - Lu, Yiling AU - Mills, Gordon B. AU - Cho, Raymond J. AU - Collisson, Eric A. AU - van’t Veer, Laura J. AU - Spellman, Paul T. AU - Gray, Joe W. PY - 2013 DA - 2013/12/10 TI - Modeling precision treatment of breast cancer JO - Genome Biology SP - R110 VL - 14 IS - 10 AB - First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. SN - 1474-760X UR - https://doi.org/10.1186/gb-2013-14-10-r110 DO - 10.1186/gb-2013-14-10-r110 ID - Daemen2013 ER -