title: BGRMI: A method for inferring gene regulatory networks from time-course gene expression data and its application in breast cancer research.
abstract: Reconstructing gene regulatory networks (GRNs) from gene expression data is a challenging problem. Existing GRN reconstruction algorithms can be broadly divided into model-free and model-based methods. Typically, model-free methods have high accuracy but are computation intensive whereas model-based methods are fast but less accurate. We propose Bayesian Gene Regulation Model Inference (BGRMI), a model-based method for inferring GRNs from time-course gene expression data. BGRMI uses a Bayesian framework to calculate the probability of different models of GRNs and a heuristic search strategy to scan the model space efficiently. Using benchmark datasets, we show that BGRMI has higher/comparable accuracy at a fraction of the computational cost of competing algorithms. Additionally, it can incorporate prior knowledge of potential gene regulation mechanisms and TF hetero-dimerization processes in the GRN reconstruction process. We incorporated existing ChIP-seq data and known protein interactions between TFs in BGRMI as sources of prior knowledge to reconstruct transcription regulatory networks of proliferating and differentiating breast cancer (BC) cells from time-course gene expression data. The reconstructed networks revealed key driver genes of proliferation and differentiation in BC cells. Some of these genes were not previously studied in the context of BC, but may have clinical relevance in BC treatment.
authors.affiliation: Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Republic of Ireland.
authors.forename: Luis F
authors.initials: LF
authors.lastname: Iglesias-Martinez
authors.affiliation: Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Republic of Ireland.|Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland.
authors.forename: Walter
authors.initials: W
authors.lastname: Kolch
authors.affiliation: Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Republic of Ireland.
authors.forename: Tapesh
authors.initials: T
authors.lastname: Santra
mesh_terms: D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000235:genetics*; D002454:Cell Differentiation; D049109:Cell Proliferation; D019295:Computational Biology; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D008954:Models, Biological; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D059467:Transcriptome