COBRE: UID: PROJ 4: COMPUTATIONAL & MATHEMATICAL ANALYSIS OF BIOMEDICAL DATA

COBRE：UID：项目 4：计算

• 批准号: 7720638
• 负责人: James A. Foster
• 金额: $ 38.1万
• 依托单位: UNIVERSITY OF IDAHO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-05-15 至 2009-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7720638
• 关键词: Algorithms; Alleles; Antibiotic Resistance; Centers of Research Excellence; Computer Retrieval of Information on Scientific Projects Database; Computers; Data; Discipline; Evolution; Exclusion; Faculty; Funding; Genes; Goals; Grant; Growth and Development function; Institution; Learning; Methods; Microbe; Microbial Biofilms; Modeling; Performance; Phylogeny; Population; Problem Solving; Process; Research; Research Personnel; Resources; Scientist; Source; Statistical Models; Students; Testing; Theoretical model; United States National Institutes of Health; Virulent; Work; disease transmission; improved; interest; member; microbial; migration; predictive modeling; programs

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The long-term goal of this project is to detect, predict, and explain the evolutionary processes being explored in projects 1-3. The faculty researchers participating in this project interact with each other and with the researchers working on projects 1-3. We have developed and enhanced theoretical models describing different aspects of evolutionary processes, such as epistatic interactions between genes, the effects of migration and spatial restrictions on evolving populations, and the emergence of microbial consortia in biofilms. We have also developed new, highly efficient, algorithms and statistical models for aligning sequences and inferring phylogenies. In all cases, we have tested our methods on empirical data, usually generated by other COBRE researchers. With these data, we have refined our algorithms and models, either by improving or better quantifying their performance. These results are significant in that they mark progress toward more realistic and predictive models of evolutionary processes, such as acquired antibiotic resistance, competitive exclusion, the spread of virulent microbes, or the transmission of disease related alleles. In addition, two new faculty members have joined this effort. Dr. Frank Gao is a mathematician who has taken a six-month sabbatical with Dr. Larry Forney to learn about biofilm growth and development with the intent to develop a new research program on modeling adaptive evolution in microbial biofilms. Dr. Chris Williams is a statistician who has taken a one-year sabbatical to and Consequently, this paragraph presents an overview of the activities in this project. We have demonstrated that mathematicians, computer scientists, and biologists can productively collaborate to solve problems of significant interest to each of the three disciplines. This has proven true with interactions involving faculty, students, and postdocs.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 该项目的长期目标是检测、预测和解释项目 1-3 中正在探索的进化过程。参与该项目的教员研究人员相互交流，并与从事项目 1-3 的研究人员进行交流。我们开发并增强了描述进化过程不同方面的理论模型，例如基因之间的上位相互作用、迁移和空间限制对进化种群的影响，以及生物膜中微生物群落的出现。我们还开发了新的高效算法和统计模型，用于比对序列和推断系统发育。在所有情况下，我们都根据经验数据测试了我们的方法，这些数据通常由其他 COBRE 研究人员生成。借助这些数据，我们通过改进或更好地量化算法和模型的性能来完善算法和模型。这些结果意义重大，因为它们标志着进化过程的更现实和预测模型的进展，例如获得性抗生素耐药性、竞争排斥、有毒微生物的传播或疾病相关等位基因的传播。此外，两名新教师也加入了这项工作。 Frank Gau 博士是一位数学家，他与 Larry Forney 博士一起度过了为期六个月的休假，以了解生物膜的生长和发育，旨在开发一个关于微生物生物膜适应性进化建模的新研究项目。 Chris Williams 博士是一位统计学家，他已经休了一年的休假，因此，本段概述了该项目的活动。我们已经证明，数学家、计算机科学家和生物学家可以有效地合作解决这三个学科中各自感兴趣的问题。这在教师、学生和博士后的互动中得到了证明。