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.

生物信息学研究和基因组序列比对尤其彻底改变了人们对细胞如何工作的理解。基因组序列比对识别单个基因序列之间的相似区域，这些区域可能是序列之间功能或进化关系的结果。然而，细胞中的基因和其他生物分子并不是孤立地发挥作用的。取而代之的是，它们相互作用以维持一个人的生命。这正是生物网络(BNS)的模型：在BNS中，生物分子被表示为节点，生物分子之间的物理或功能相互作用被表示为边。因此，BN比对旨在确定不同物种BN之间在拓扑和功能上的相似区域，有望进一步深入了解生命、进化、疾病和治疗的组织原则。例如，它可以指导生物知识在保守的(排列的)网络区域之间跨物种的转移。这一点很重要，因为BNS中的许多节点目前即使对于研究充分的模式物种也没有功能特征。智能优点：本项目旨在解决当前网络对齐问题的几个问题。首先，它将开发一个新的框架，用于公平评估现有的BN比对方法，这是目前所缺乏的。其次，它将重新定义网络对齐问题，以允许直接优化保留的网络拓扑量，而这是当前方法无法做到的。第三，由于存在不同类型的BN来捕获小区的不同功能切片，并且由于现有方法只能对齐同类网络，而忽略任何节点或边缘类型，因此本项目将扩展所提出的方法以允许对包括不同BN类型的异类网络进行对齐。所提出的方法将用于两个新的跨学科协作应用：1)研究酿酒酵母和人类蛋白酶体在蛋白质降解中的作用；2)研究疟原虫家族寄生虫的致病性和耐药性。更广泛的影响：BN对齐有着广泛的应用。例如，它可以用于在相似的网络区域之间将生物知识从注释良好的物种转移到注释较差的物种，或者根据物种BN的相似性来推断物种的系统发育和进化关系。除了计算生物学，这个项目还可能影响其他领域。例如，网络对齐可以使在线社交网络去匿名化，从而影响用户隐私。由于网络研究跨越许多领域，因此将向来自不同学科的研究人员提供实现所提出方法的免费开源软件工具。该软件还将作为一种教育工具。