Paper Info
Title
Discovering dysregulated phenotype-related gene patterns
Abstract
With the abundance of vast amounts of \"-omic\" biological data from multiple sources that span diverse biological processes, approaches for answering critical questions become a vital mission. To grasp more comprehensive view of the biology of the organism, recent research has focused on integrating multiple sources of data. This integration provides more insights and helps reduce the impact of problems each source may have. Recent research showed that differentially expressed, or dysregulated, patterns of interacting proteins exhibit more interesting properties with respect to many complex phenotypes. In this work we follow an integrative approach by combining the physical protein-protein interaction, PPI, network with gene expression data for a number of diseases and phenotypes. In this study, we propose an algorithm for mining Dysregulated Phenotype-Related interacting genes, DPRs. Experimental results on 88 Human gene expression datasets that were annotated by employing UMLS mapping demonstrate the effectiveness of the algorithm in discovering biologically and statistically significant DPRs.
Year
DOI
Venue
2014
10.1145/2649387.2649441
BCB
Keywords
Field
DocType
graphs and networks,-omic,dpr,theory,network problems,phenotype,biological,dysregulated,omic
Biological data,Gene,Biology,Phenotype,Bioinformatics,Unified Medical Language System,Organism
Conference
Citations 
PageRank 
References 
0
0.34
11
Authors
2
Name
Order
Citations
PageRank
Rami Alroobi111.38
Saeed Salem218217.39