B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

作     者：Fadi Towfic Shakti Gupta Vasant Honavar Shankar Subramaniam 

作者机构：Bioinformatics and Computational Biology Graduate ProgramIowa State UniversityAmesIA 50010USA Department of BioengineeringUniversity of California at San DiegoLa JollaCA 92122USA 

出 版 物：《Genomics, Proteomics & Bioinformatics》 (基因组蛋白质组与生物信息学报（英文版）)

年 卷 期：2012年第10卷第3期

页      面：142-152页

核心收录：

学科分类：0710[理学-生物学] 1001[医学-基础医学(可授医学、理学学位)] 07[理学] 071007[理学-遗传学] 0714[理学-统计学（可授理学、经济学学位）] 0703[理学-化学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：funded by the National Science Foundation (NSF) Grant (DGE0504304) to Iowa State University and NSF Grants 0939370 0835541 and 0641037 awarded to SS 

主　　题：Ligand recognition B-cells Gene coexpression network alignment 

摘      要：The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Col- lectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG path- ways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches （e.g., gene coexpression network alignment algorithms） in elucidating biochemical pathways involved in complex signaling events in ceils.