IIBR Informatics: Integrating codon evolution and sequence-assembly error models into multiple sequence alignment

信息时代从根本上改变了大多数科学领域的运作方式。基因组学和信息学的进步从根本上重塑了生命科学，产生了影响包括医学和农业在内的多个战神的创新。该项目将设计新的计算方法和软件来管理现代基因组数据集的复杂性，解决现有方法忽视的挑战。由于计算训练对现代生物学学生至关重要，本项目将通过对地区、社区和部落学院的教师和讲师进行培训，以实证为基础，向学生传授计算技能，从而扩大计算的参与度。本项目将开发新的计算方法，使用针对现代数据集挑战进行优化的统计模型来分析遗传数据。首先，将开发新的有限状态传感器模型，用于对齐遗传和基因组序列，这些序列捕获塑造现代数据集的生物和技术过程。其次，这些模型将在COATi中实现，COATi是一种新的多序列比对工具，将是免费和开源的。第三，COATi将被用来理解未充分研究的分子进化特征。此外，将为地区，社区和部落学院的教师举办软件木工教练培训讲习班，这将提高这些机构的计算教学质量，从而扩大来自代表性不足和服务不足背景的学生对计算的参与。该项目的结果可在www.example.com上获得https://cartwrig.ht/coati/.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

The information age has fundamentally changed the way most areas of science operate. Advances in genomics and informatics have radically reshaped the life sciences, producing innovations that impact multiple ares including medicine and agriculture. This project will design new computational methods and software to manage the complexities of modern genomic datasets, addressing challenges that existing approaches have overlooked. As computational training is essential for modern biology students, this project will broaden the participation in computing by training faculty and instructors at regional, community, and tribal colleges in evidence-based practices for teaching computing skills to students.This project will develop new computational methods to analyze genetic data using statistical models that are optimized for the challenges of modern datasets. First, new finite-state transducer models will be developed for aligning genetic and genomic sequences that capture the biological and technical process that shape modern datasets. Second, these models will be implemented in COATi, a new multiple-sequence alignment tool that will be free and open-sourced. Thirdly, COATi will be used to understand understudied features of molecular evolution. In addition, Software Carpentry Instructor training workshops will be held for faculty at regional, community, and tribal colleges, which will improve the quality of computational instruction at these institutions, and thus broaden the participation in computing for students from underrepresented and underserved backgrounds. The results of the project are available at https://cartwrig.ht/coati/.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.