CAREER: Quantitative Analysis of Endocrine Disrupting Chemicals

0951613 -Kreeger EDC对细胞信号传导和行为影响的实验和计算分析是解决这一挑战性问题的创新方法。迭代实验模型实验设计将能够发现EDC治疗特别影响的机制。此外，所提出的在计算机上生成信号数据集的方法将导致新的建模技术的开发和原始模型的改进，以处理暴露于EDC组合的复杂和多变量问题。最终目标是开发能够解释ER信号在正常和疾病状态下的复杂作用的模型，这是解决妇女健康问题的重要组成部分。 内分泌干扰物的影响是一个全球性的问题，提出的系统生物学方法是必不可少的，以应对问题的复杂性。开发计算机模型来识别内分泌干扰物影响的细胞机制并预测暴露于组合的结果是防止内分泌干扰物有害影响的重要一步。此外，实验数据收集和模型开发和分析的概述框架可以应用于基本上任何生物网络，为未来研究雌激素信号对细胞行为的影响提供基础。概述的建议，将学生从非博士授予机构进入研究实验室，并进行推广到K-12学生将有助于培养下一代的学生在数学生物学接口培训，并将装备学生和研究员在实验室培训有效的跨学科研究人员和教师。

0951613 - KreegerThe experimental and computational analysis of EDC impact on cellular signaling and behavior is an innovative approach to address this challenging problem. The iterative experiment model experiment design will enable the discovery of mechanisms that are specifically impacted by EDC treatment. Additionally, the proposed methods to generate signaling data sets in silico will lead to the development of new modeling techniques and refinement of the original model to handle the complicated and multivariate problem of exposure to EDC combinations. The ultimate goal is to develop models that can interpret the complicated role of ER signaling in both normal and disease states, which is an essential component of addressing women's health concerns. The effects of EDCs are a global concern and the proposed systems biology methods are essential to contend with the complexity of the problem. Development of in silico models to identify cellular mechanisms that EDCs impact and predict the result of exposure to combinations is an essential step towards preventing harmful effects from EDCs. Additionally, the outlined framework of experimental data collection and model development and analysis can be applied to essentially any biological network, providing the basis for future studies of the impact of estrogenic signaling on cellular behavior. The outlined proposal to incorporate students from non-PhD granting institutions into the research laboratory and to perform outreach to K-12 students will help to develop the next generation of students trained at the math-biology interface, and will equip students and fellows trained in the laboratory to be effective interdisciplinary researchers and teachers.