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

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 这个项目的长期目标是检测、预测和解释项目1-3中探索的进化过程。参与该项目的教师研究人员相互交流，并与项目1-3的研究人员进行交流。我们已经开发和增强了描述进化过程的不同方面的理论模型，如基因间的上位相互作用，迁移和空间限制对进化种群的影响，以及生物膜中微生物财团的出现。我们还开发了新的、高效的算法和统计模型，用于比对序列和推断遗传学。在所有情况下，我们都在经验数据上测试了我们的方法，这些数据通常是由其他COBRE研究人员生成的。通过这些数据，我们改进了我们的算法和模型，无论是通过改进还是更好地量化它们的性能。这些结果是重要的，因为它们标志着进化过程的更现实和预测模型的进展，如获得性抗生素耐药性，竞争性排斥，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一努力。Frank Gao博士是一位数学家，他与Larry Forney博士一起休了六个月的假，了解生物膜的生长和发育，目的是开发一个新的研究项目，对微生物生物膜中的适应性进化进行建模。克里斯威廉姆斯博士是一名统计学家，他休了一年的假，因此，本段概述了本项目的活动。我们已经证明，数学家，计算机科学家和生物学家可以富有成效地合作，以解决这三个学科中的每一个都感兴趣的问题。这已经证明了真正的互动涉及教师，学生和博士后。

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.