Effective identification of conserved pathways in biological networks using hidden Markov models.-猫眼课题宝

DOI：

10.1371/journal.pone.0008070

发表时间：

2009-12-07

期刊：

PloS one

影响因子：

3.7

通讯作者：

中科院分区：

综合性期刊3区

文献类型：

作者：

Qian X;Yoon BJ

来源链接：

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2782142/?report=classic

各种用于测量分子相互作用的高通量实验技术的出现使得在全球范围内系统地研究生物相互作用成为可能。由于生物过程是通过大量分子的精心协作来进行的，从而产生了一个复杂的分子相互作用网络，因此对这些生物网络的比较分析可以为生物系统的功能组织和调控机制带来重要的见解。本文提出了一种基于隐马尔可夫模型(HMM)的识别不同生物生物网络中常见相互作用模式的有效框架。在给定两个或多个网络的情况下，我们的方法可以有效地在各自的网络中找到最匹配的路径，其中匹配路径可以包含灵活数量的连续插入和删除。基于从相互作用蛋白质数据库(DIP)和其他公共数据库中获得的几个蛋白质-蛋白质相互作用(PPI)网络，我们证明了我们的方法能够检测到跨不同生物保守的生物学意义上的通路。我们的算法具有随着对齐路径的大小而线性增长的多项式复杂度。这使得在台式计算机上能够在几分钟内搜索具有10个以上节点的非常长的路径。根据作者的要求，可以获得实现该算法的软件程序。

The advent of various high-throughput experimental techniques for measuring molecular interactions has enabled the systematic study of biological interactions on a global scale. Since biological processes are carried out by elaborate collaborations of numerous molecules that give rise to a complex network of molecular interactions, comparative analysis of these biological networks can bring important insights into the functional organization and regulatory mechanisms of biological systems. In this paper, we present an effective framework for identifying common interaction patterns in the biological networks of different organisms based on hidden Markov models (HMMs). Given two or more networks, our method efficiently finds the top matching paths in the respective networks, where the matching paths may contain a flexible number of consecutive insertions and deletions. Based on several protein-protein interaction (PPI) networks obtained from the Database of Interacting Proteins (DIP) and other public databases, we demonstrate that our method is able to detect biologically significant pathways that are conserved across different organisms. Our algorithm has a polynomial complexity that grows linearly with the size of the aligned paths. This enables the search for very long paths with more than 10 nodes within a few minutes on a desktop computer. The software program that implements this algorithm is available upon request from the authors.