Breast cancer is the most commonly diagnosed cancer, and the second leading cause of cancer deaths among American women. As such, breast cancer has been identified as a public health priority in the United States. Despite this clinical and social importance, we are only now beginning to understand the molecular, cellular, and developmental mechanisms underlying breast cancer initiation and progression in enough detail to allow rudimentary predictions of treatment response to be made. Mathematical modeling and computational simulation offers the extraordinary promise of integrating huge quantities of diverse data into coherent developmental and predictive models capable of informing """"""""personalized medicine"""""""" decisions. However, these models can only be as good as our biological understanciing of the parameters involved in breast cancer development, and as the experimental data on which they are based. Our educational and training plan is designed to fill a need for an organized training process in combined biological and mathematical/computational modeling of breast cancer for postdoctoral fellows and undergraduates. In subsequent funding cycles, we intend to extend this training program to include graduate student trainees. Our proposed training program brings together, in a formal way, researchers from clinical, translational, and basic science areas of experimental breast cancer research, as well as researchers in the areas of mathematical modeling, computational biology and bioinformatics with a keen interest in working toward a common goal of understanding breast cancer biology. In this proposal, we will establish two unique multidisciplinary training programs, one for undergraduates and one for postdoctoral trainees. The undergraduate program will be entitled the """"""""Multidisciplinary Summer Undergraduate Training Program in Experimental and Mathematical Modeling of Cancer."""""""" This program will be geared toward individuals exploring their interest in cancer research and will serve to introduce undergraduates to various aspects of experimental biology and to mathematical/computational modeling approaches and analyses. The multidisciplinary postdoctoral training program will be geared toward recruitment and training of individuals holding Ph.D. or M.D./Ph.D. degrees in mathematical modeling, computational biology, biostatistics/bioinformatics, or a related advanced degree who are interested in gaining significant experimental experience and deeper conceptual insight into breast cancer development in a laboratory or clinical setting. Prospective candidates will be teamed both with a basic science/clinical mentor, and a mathematical modeling/computational biology mentor, for the development of a suitable research project addressing an important unanswered question in breast cancer biology from a combined experimental and mathematical/computational perspective.
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