Uncover cooperative gene regulations by microRNAs and transcription factors in glioblastoma using a nonnegative hybrid factor model

Transcriptional regulation by transcription factors (TFs) and microRNAs controls when and how much RNA is created. Due to technical limitations, the protein level expressions of TFs are usually unknown, making computational reconstruction of transcriptional network a difficult task. We proposed here a novel Bayesian non negative hybrid factor model for transcriptional network modeling, which is capable to estimate both the non-negative abundances of the transcription factors, the regulatory effects of TFs and microRNAs, and the sample clustering information by integrating microarray data and existing knowledge regarding TFs and microRNAs regulated target genes. The results demonstrated its validity and effectiveness to reconstructing transcriptional networks through simulated systems and real data.