title: cGRNB: a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets.
abstract: BACKGROUND
  We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts.
  
  
  METHODS
  In this work, we compiled putative TF-gene, miRNA-gene and TF-miRNA regulatory relationships from forward-engineering pipelines and curated them as built-in data libraries. We streamlined the R codes of our two separate forward-and-reverse engineering algorithms for combinatorial gene regulatory network construction and formalized them as two major functional modules. As a result, we released the cGRNB (combinatorial Gene Regulatory Networks Builder): a web server for constructing combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. The cGRNB enables two major network-building modules, one for MPGE (miRNA-perturbed gene expression) datasets and the other for parallel miRNA/mRNA expression datasets. A miRNA-centered two-layer combinatorial regulatory cascade is the output of the first module and a comprehensive genome-wide network involving all three types of combinatorial regulations (TF-gene, TF-miRNA, and miRNA-gene) are the output of the second module.
  
  
  CONCLUSIONS
  In this article we propose cGRNB, a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. Since parallel miRNA/mRNA expression datasets are rapidly accumulated by the advance of next-generation sequencing techniques, cGRNB will be very useful tool for researchers to build combinatorial gene regulatory networks based on expression datasets. The cGRNB web-server is free and available online at http://www.scbit.org/cgrnb.
authors.forename: Huayong
authors.initials: H
authors.lastname: Xu
authors.forename: Hui
authors.initials: H
authors.lastname: Yu
authors.forename: Kang
authors.initials: K
authors.lastname: Tu
authors.forename: Qianqian
authors.initials: Q
authors.lastname: Shi
authors.forename: Chaochun
authors.initials: C
authors.lastname: Wei
authors.forename: Yuan-Yuan
authors.initials: YY
authors.lastname: Li
authors.forename: Yi-Xue
authors.initials: YX
authors.lastname: Li
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks; D020407:Internet; D035683:MicroRNAs / Q000235:genetics; D012984:Software; D014157:Transcription Factors / Q000378:metabolism; D059467:Transcriptome
chemical_list: D035683:MicroRNAs; D014157:Transcription Factors