Systematic Identification of Transcriptional and Post-Transcriptional Regulations in Human Respiratory Epithelial Cells during Influenza A Virus Infection กก Introduction: Welcome to our website! This is an webpage for our paper "Systematic Identification of Transcriptional and Post-Transcriptional Regulations in Human Respiratory Epithelial Cells during Influenza A Virus Infection". In the paper, we proposed a novel method to identify transcriptional and post-transcriptional regulations from time-course mRNA and miRNA expression data. We formulated the identification problem to a constrained LASSO and combined it with the dynamic Bayesian network (DBN) model to identify the activated regulatory relationships from time-course expression data after influenza A virus infection. You can find the source data, source code which have been referred in the paper. Pay attention to the users: You can use and redistribute the data and code if you accept GNU General Public License (GPL). Source Data: 1. Human background regulatory network (TF, miRNA, gene, ID mapping) 2. Preprocessed gene expression data 3. 303 regulatory modules 4. Active regulatory relationships กก Source code: Download กก Reference: Liu ZP, et al. Systematic Identification of Transcriptional and Post-Transcriptional Regulations in Human Respiratory Epithelial Cells during Influenza A Virus Infection. In Submission. Note: This version of the program is in very preliminary stage and is provided just for testing purpose. The program is still under development. Any comments and questions, please do not hesitate to contact: zpliu(at)amss.ac.cn Last update: 2013/09/05