Education, Traning, and Outreach Program

乳腺癌是最常见的癌症，也是癌症死亡的第二大原因 在美国女性中。因此，乳腺癌已被确定为美国的公共卫生优先事项。 States.尽管具有这种临床和社会重要性，但我们现在才开始了解分子， 乳腺癌发生和发展的细胞和发育机制， 允许对治疗反应进行初步预测。数学建模和计算 仿真提供了将大量不同的数据整合成连贯的 发展和预测模型能够告知“个性化医疗”的决定。但这些 模型只能和我们对乳腺癌相关参数的生物学理解一样好 发展，并作为他们所依据的实验数据。 我们的教育和培训计划旨在满足以下方面对有组织的培训过程的需求： 乳腺癌的生物学和数学/计算模型 研究员和本科生。在随后的资金周期中，我们打算将这一培训计划扩展到 包括研究生学员。 我们提出的培训计划汇集了，在一个正式的方式，研究人员从临床，翻译， 实验性乳腺癌研究的基础科学领域，以及数学领域的研究人员 建模，计算生物学和生物信息学，对实现以下共同目标有浓厚的兴趣： 了解乳腺癌生物学。在这项建议中，我们将建立两个独特的多学科培训 计划，一个本科生和一个博士后实习生。 本科课程将被命名为“多学科暑期本科培训计划” 癌症的实验和数学建模。“这个项目将面向个人探索 他们对癌症研究的兴趣，并将有助于向本科生介绍实验的各个方面。 生物学以及数学/计算建模方法和分析。 多学科博士后培训计划将面向招聘和培训 拥有博士学位的个人或医学博士/博士数学建模，计算生物学， 生物统计学/生物信息学，或相关的高级学位谁有兴趣获得重要的实验 在实验室或临床环境中对乳腺癌发展的经验和更深层次的概念性见解。 潜在的候选人将与基础科学/临床导师和数学导师一起工作。 建模/计算生物学导师，用于开发合适的研究项目， 乳腺癌生物学中重要的未回答的问题， 数学/计算视角

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.