Education, Traning, and Outreach Program

乳腺癌是最常见的诊断癌症，也是导致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公共卫生的优先事项 各州。尽管这种临床和社会重要性，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足够详细 允许对治疗反应进行初步预测。数学建模和计算 模拟提供了将大量不同数据整合成连贯数据的非凡前景 能够为“个性化医疗”决策提供信息的发展和预测模型。然而，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，并作为它们所依据的实验数据。 我们的教育和培训计划旨在满足在 用于博士后的乳腺癌生物学和数学/计算联合建模 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 包括研究生实习生。 我们建议的培训计划以正式的方式汇集了来自临床、翻译和 基础科学领域的实验性乳腺癌研究，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兴趣浓厚 了解乳腺癌生物学。在这项提议中，我们将建立两个独特的多学科培训 项目，一个面向本科生，一个面向博士后实习生。 本科项目将被命名为“多学科暑期本科培训项目” 在癌症的实验和数学建模中。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 生物学和数学/计算建模方法和分析。 多学科博士后培训计划将面向以下人员的招聘和培训 拥有数学建模、计算生物学或医学博士/博士学位的个人， 生物统计学/生物信息学或相关高级学位，有兴趣获得有意义的实验 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洞察。 未来的候选人将与基础科学/临床导师和数学专家合作 建模/计算生物学导师，用于开发适当的研究项目 乳腺癌生物学中一个重要的悬而未决的问题--来自联合实验和 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.