CAREER: An Integrated Approach to the Study of Biological Process Specific Networks

普林斯顿大学获得了教师早期职业发展计划（Career）的资助，用于开发一种综合计算和实验方法来模拟生物途径和网络。该技术将由三个集成组件组成：一个用于多种基因组数据的可推广、高效和准确集成的计算组件，一个用于基于集成数据的网络/路径建模的分析组件，以及一个用于验证和反馈的实验组件。多种基因组数据的综合分析和实验验证将允许计算方法的迭代改进，并导致高度精确的网络级途径模型，可以作为复杂生物过程的机制模型的支架。这项工作的关键贡献在于计算建模和实验测试的紧密集成，以创建一种组合方法，该方法使用预测的迭代改进来改进模型和算法。这种综合方法的成功将导致比纯计算方法创建的生物过程和途径更精确和完整的模型，但它将比单独通过实验研究相同过程要快得多。该提案的跨学科性质将进一步推动高级计算机科学对生物学的影响，并将通过研究和跨学科教育促进这两个领域之间的进一步互动。与此研究计划相配合，将开发两门生物信息学研究生课程。PI还将继续与Lewis-Sigler综合基因组学研究所的生物学、物理学和化学教师合作，参与本科生跨学科基因组学课程的开发和教学。普林斯顿大学开发的本科和研究生课程材料都将通过互联网提供。此外，将在普林斯顿大学组织一个系统生物学研讨会，以促进计算和实验研究人员之间的合作，并向更多的学生介绍系统生物学。

Princeton University is awarded a grant from the Faculty Early Career Development program (CAREER) to develop an integrated computational and experimental approach for modeling biological pathways and networks. This technology will consist of three integrated components: a computational component for generalizable, efficient, and accurate integration of diverse genomic data, an analytical component for network/pathway modeling based on the integrated data, and an experimental component for validation and feedback. The integrated analysis of diverse genomic data and experimental verification will allow iterative refinement of computational methods and lead to highly accurate network-level pathway models that can serve as a scaffold for mechanistic models of complex biological processes. The key contribution of this work is in the tight integration of computational modeling and experimental testing to create a combined approach that uses iterative refinement of predictions to improve both the models and the algorithms. The success of this integrated approach will lead to more accurate and complete models of biological processes and pathways than those created by purely computational methods, and yet it will be substantially faster than study of the same processes by experimentation alone. The interdisciplinary nature of this proposal will further the impact of advanced computer science on biology and will precipitate further interactions between the two fields, both through research and through interdisciplinary education. In concert with this research program, two graduate courses in bioinformatics will be developed. The PI will also continue to participate in development and teaching of a cross-disciplinary genomics curriculum for undergraduates in collaboration with biology, physics, and chemistry faculty at the Lewis-Sigler Institute for Integrative Genomics. Both undergraduate and graduate curricular materials developed at Princeton will be made available via the Internet. In addition, a systems biology symposium at Princeton University will be organized to catalyze collaboration among computational and experimental researchers and to introduce more students to systems biology.