title: A novel motif-discovery algorithm to identify co-regulatory motifs in large transcription factor and microRNA co-regulatory networks in human.
abstract: BACKGROUND
  Interplays between transcription factors (TFs) and microRNAs (miRNAs) in gene regulation are implicated in various physiological processes. It is thus important to identify biologically meaningful network motifs involving both types of regulators to understand the key co-regulatory mechanisms underlying the cellular identity and function. However, existing motif finders do not scale well for large networks and are not designed specifically for co-regulatory networks.
  
  
  RESULTS
  In this study, we propose a novel algorithm CoMoFinder to accurately and efficiently identify composite network motifs in genome-scale co-regulatory networks. We define composite network motifs as network patterns involving at least one TF, one miRNA and one target gene that are statistically significant than expected. Using two published disease-related co-regulatory networks, we show that CoMoFinder outperforms existing methods in both accuracy and robustness. We then applied CoMoFinder to human TF-miRNA co-regulatory network derived from The Encyclopedia of DNA Elements project and identified 44 recurring composite network motifs of size 4. The functional analysis revealed that genes involved in the 44 motifs are enriched for significantly higher number of biological processes or pathways comparing with non-motifs. We further analyzed the identified composite bi-fan motif and showed that gene pairs involved in this motif structure tend to physically interact and are functionally more similar to each other than expected.
  
  
  METHODS
  CoMoFinder is implemented in Java and available for download at http://www.cs.utoronto.ca/∼yueli/como.html.
authors: College of Computer Science and Electronic Engineering, Hunan University, Changsha, Hunan, China and.
authors: Cheng
authors: C
authors: Liang
authors: Department of Computer Science, Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.
authors: Yue
authors: Y
authors: Li
authors: College of Computer Science and Electronic Engineering, Hunan University, Changsha, Hunan, China and.
authors: Jiawei
authors: J
authors: Luo
authors: Department of Computer Science, Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.
authors: Zhaolei
authors: Z
authors: Zhang
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D015894:Genome, Human; D006801:Humans; D035683:MicroRNAs / Q000502:physiology*; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics*; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D035683:MicroRNAs; D014157:Transcription Factors