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

职业：生物过程特定网络研究的综合方法

• 批准号: 0546275
• 负责人: Olga Troyanskaya
• 金额: $ 100.07万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-06-01 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0546275&HistoricalAwards=false
• 关键词: CAREER; Integrated; Approach; Study; Biological

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.

普林斯顿大学获得了教师早期职业发展计划(Career)的资助，以开发一种集成的计算和实验方法来模拟生物路径和网络。这项技术将由三个集成组件组成：用于概括、高效和准确整合各种基因组数据的计算组件，用于基于集成数据的网络/通路建模的分析组件，以及用于验证和反馈的实验组件。对各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，并导致高精度的网络级通路模型，这些模型可以作为复杂生物过程的机械模型的支架。这项工作的关键贡献是将计算建模和实验测试紧密结合起来，以创建一种组合方法，使用迭代预测精细化来改进模型和算法。这种综合方法的成功将导致生物过程和途径的模型比纯粹的计算方法建立的模型更准确和完整，但它将比仅通过实验研究相同的过程快得多。这一建议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。与这项研究计划相配合，将开发两门生物信息学研究生课程。该研究所还将继续与刘易斯-西格勒综合基因组学研究所的生物、物理和化学教师合作，为本科生参与跨学科基因组学课程的开发和教学。普林斯顿大学编写的本科生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次系统生物学研讨会，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。