AF: Small: Novel Directions for Biological Network Alignment

AF：小：生物网络对齐的新方向

• 批准号: 1319469
• 负责人: Tijana Milenkovic
• 金额: $ 44.49万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1319469&HistoricalAwards=false
• 关键词: AF; Small; Novel; Directions; Biological

Bioinformatics research and genomic sequence alignment in particular have revolutionized the understanding of how cells work. Genomic sequence alignment identifies regions of similarity between sequences of individual genes that are a likely consequence of functional or evolutionary relationships between the sequences. However, genes and other biomolecules in the cells do not function in isolation. Instead, they interact with each other to keep one alive. And this is exactly what biological networks (BNs) model: in BNs, biomolecules are represented as nodes and physical or functional interactions between the biomolecules are represented as edges. Thus, BN alignment, which aims to identify topologically and functionally similar regions between BNs of different species, is promising to give further insights into organizational principles of life, evolution, disease, and therapeutics. For example, it could guide the transfer of biological knowledge across species between the conserved (aligned) network regions. This is important, since many nodes in BNs are currently functionally uncharacterized even for well-studied model species. Intellectual Merit: This project aims to address several issues with the current view of the problem of network alignment. First, it will develop a novel framework for fair evaluation of existing BN alignment methods, which is currently lacking. Second, it will redefine the problem of network alignment to allow for directly optimizing the amount of conserved network topology, which current methods fail to do. Third, since different types of BNs exist that capture different functional slices of the cell, and since the existing methods can align only homogeneous networks, ignoring any node or edge types, this project will extend the proposed methods to allow for alignment of heterogeneous networks encompassing the different BN types. The proposed methods will be used in two novel interdisciplinary collaborative applications: 1) studying the role of yeast S. cerevisiae and human proteasomes responsible for protein degradation, and 2) studying pathogenicity and drug resistance of malaria parasites from the Plasmodium family. Broader Impact: BN alignment has broad applications. For example, it can be used to transfer biological knowledge from well annotated to poorly annotated species between similar network regions or to infer species' phylogenetic and evolutionary relationships based on similarities of their BNs. Besides computational biology, this project may impact other domains as well. For example, network alignment can de-anonymize online social networks and thus impact user privacy. Since network research spans many domains, a free open-source software tool implementing the proposed methods will be offered to researchers from diverse disciplines. The software will also serve as an educational tool.

尤其是生物信息学研究和基因组序列比对彻底改变了对细胞工作方式的理解。基因组序列比对识别单个基因序列之间相似性的区域，这可能是序列之间功能或进化关系的结果。但是，细胞中的基因和其他生物分子不能孤立起作用。相反，他们相互互动以保持一个人的活力。这正是生物网络（BNS）模型：在BNS中，生物分子表示为节点和生物分子之间的物理或功能相互作用，表示为边缘。因此，旨在识别不同物种BN之间拓扑和功能相似的区域的BN对准有望进一步深入了解生命，进化，疾病和治疗学的组织原理。例如，它可以指导在保守（对齐）网络区域之间的生物学知识转移。这很重要，因为BN中的许多节点目前在功能上也没有表征，即使对于经过良好的模型物种也是如此。知识分子的优点：该项目旨在解决有关网络一致性问题的当前观点的几个问题。首先，它将开发一个新颖的框架，以公平地评估现有的BN一致性方法，该方法目前缺乏。其次，它将重新定义网络对齐问题，以直接优化当前方法无法做到的保守网络拓扑数量。第三，由于存在捕获单元格的不同功能切片的不同类型的BN，并且由于现有方法只能对齐均匀的网络，而忽略任何节点或边缘类型，因此该项目将扩展所提出的方法以允许对包含不同BN类型的异质网络对齐。所提出的方法将用于两个新型的跨学科协作应用中：1）研究酵母菌葡萄球菌和负责蛋白质降解的人类蛋白酶体的作用，以及2）研究疟原虫对疟原虫的致病性和耐药性。 更广泛的影响：BN对齐有广泛的应用。例如，它可用于将生物学知识从相似的网络区域之间的良好注释转移到注释不良的物种，或者基于BN的相似性推断物种的系统发育和进化关系。除了计算生物学外，该项目还可能影响其他领域。例如，网络对齐可以将在线社交网络取消匿名化，从而影响用户隐私。由于网络研究涵盖了许多领域，因此将向来自不同学科的研究人员提供实施该方法的免费开源软件工具。该软件还将用作教育工具。