AF: Small: Novel Directions for Biological Network Alignment

特别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个体基因的序列之间的相似性区域，其是序列之间的功能或进化关系的可能结果。然而，细胞中的基因和其他生物分子并不孤立地发挥作用。相反，它们相互作用，以保持一个活着。这正是生物网络（BN）的模型：在BN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缘。因此，BN对齐，其目的是确定不同物种的BN之间的拓扑结构和功能相似的区域，是有希望给进一步的见解，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（对齐）网络区域之间的跨物种转移。这是很重要的，因为许多节点的BN目前功能不明，即使是充分研究的模型物种。智力优点：这个项目的目的是解决几个问题与网络对齐的问题的当前观点。首先，它将开发一个新的框架，公平评估现有的BN对齐方法，这是目前缺乏的。其次，它将重新定义网络对齐的问题，以允许直接优化保守的网络拓扑结构的数量，这是目前的方法无法做到的。第三，由于存在捕获细胞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同构网络，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齐包含不同BN类型的异构网络。所提出的方法将用于两个新的跨学科合作应用：1）研究酵母S。酿酒酵母和负责蛋白质降解的人蛋白酶体，和2）研究疟原虫家族的疟原虫的致病性和耐药性。 更广泛的影响：BN对齐具有广泛的应用。例如，它可以用于在相似的网络区域之间将生物学知识从注释良好的物种转移到注释不良的物种，或者基于它们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，这个项目也可能影响其他领域。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，将向来自不同学科的研究人员提供一个免费的开源软件工具来实现所提出的方法。该软件还将作为一种教育工具。

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.