Postdoctoral Research Fellowship in Interdisciplinary Informatics for FY 2003

跨学科信息学博士后研究奖学金由数学和物理科学（MPS）和生物科学（BIO）董事会联合赞助，以鼓励跨越传统学科界限的研究和培训。这些奖学金为生物学和信息学的跨学科研究和教育活动提供了机会，以广泛的近期博士学位获得者（生物学家，化学家，物理学家，数学家，统计学家，计算机科学家等），他们寻求使用信息学工具和方法对生物学问题进行研究。 预计通过这些研究金培训的研究员将在培训未来的工作人员方面发挥重要作用。信息学博士后培训将允许接受生物学，数学，化学和物理科学培训的初级科学家在开发新的定量工具和方法方面发挥关键作用，这些工具和方法将推动生物学和其他领域的信息学。该奖学金的研究和培训计划的标题是“使用贝叶斯统计方法来识别共同进化的蛋白质结构域。贝叶斯系统发育方法可以识别经历了进化适应的蛋白质序列位点。本研究的目标是扩展这些方法来检测相关的突变，并使用这些信息来识别蛋白质结构域之间的相互作用位点。 这些推定的表位将与实验数据进行比较，以测试关于特定蛋白质相互作用及其在细胞网络进化中的作用的假设。

Postdoctoral Research Fellowships in Interdisciplinary Informatics are sponsored jointly by the Directorates for Mathematical and Physical Sciences (MPS) and Biological Sciences (BIO) to encourage research and training that cross the traditional disciplinary boundaries between them. These fellowships provide opportunities for interdisciplinary research and educational activities in biology and informatics to a wide range of recent doctoral recipients (biologists, chemists, physicists, mathematicians, statisticians, computer scientists, and others) who seek to conduct research on biological questions using informatics tools and methods. It is expected that the Fellows trained through these fellowships will play an important role in training the future workforce. Postdoctoral training in informatics will permit junior scientists trained in biology, mathematical, chemical, and physical sciences to play key roles in developing new quantitative tools and methods that will advance informatics in biology and other fields. The research and training plan for this fellowship is entitled "Using Bayesian statistical methods to identify coevolving protein domains." Bayesian phylogenetic methods can identify protein sequence sites that have undergone evolutionary adaptation. The goal of this research is to extend these methods to detect correlated mutations, and to use this information to identify sites of interaction between protein domains. These putative epitopes will be compared to experimental data to test hypotheses regarding specific protein interactions and their role in the evolution of cellular networks.