III-CXT:Algorithmic Tools for Determining the Organization and Dynamics of the Cell Nucleus

在这个项目中，跨学科团队建议开发一套算法工具，以促进三个重要生物学问题的研究：(a)染色体组织；(b)活细胞核染色质结构域的动力学；(c)功能位点（如复制和转录位点）的迁移特性。该项目的核心是使用计算几何和优化技术来开发有效的算法来解决一系列具有挑战性的计算问题，如集合聚类，中位数图，广义最大公共子图，几何拟合，匹配和刚性子结构提取。该项目将为所提出的问题提供一套有效的算法和优化方法。所设计的算法和技术将作为自动（或半自动）工具，准确可靠地分析细胞核组织和动态，并有助于理解基因组表达的协调。这套算法和技术将使用随机生成的数据和真实的生物数据来实施和测试。该项目的算法工具和优化方法将用于研究活细胞的细胞核。它可能会导致重大的生物学发现，并帮助我们更好地了解癌症的机制及其与染色体组织和动力学的关系。该项目将为研究生和本科生带来研究和教育机会。它将涉及来自计算机科学与工程系和生物科学系的几名研究生和本科生。

In this project, the interdisciplinary team proposes to develop a set of algorithmic tools to facilitate the study of three important biological problems: (a) Chromosome organization; (b) Dynamics of chromatin domains in the nucleus of living cells; (c) Mobility properties of functional sites (such as replication and transcription sites). The core of this project is to use computational geometry and optimization techniques to develop efficient algorithms for solving a set of challenging computational problems, such as ensemble clustering, median graph, generalized maximum common subgraphs, geometric fitting, matching, and rigid substructure extraction. This project will yield a set of efficient algorithms and optimization methods for the proposed problems. The designed algorithms and techniques will be used as automatic (or semi-automatic) tools to accurately and reliably analyze the nucleus organization and dynamics, and help understanding the coordination of genomic expression. The set of algorithms and techniques will be implemented and tested using randomly generated data and real biological data. The algorithmic tools and optimization methods from this project will be used to study the nucleus of living cells. It could potentially lead to significant biological discoveries and help us to better understand the mechanism cancers and their relationship with chromosome organization and dynamics. This project will bring research and educational opportunities to both graduate and undergraduate students. It will involve several graduate students and undergraduate students, from both Computer Science and Engineering and Biological Sciences Departments.