Search Results for "gene regulatory networks"

Living cells are complex, dynamic, self-regulatory, interactive systems, showing differential states across time and space. Complexity of cellular systems is highlighted with the multi-layered regulatory mechanisms involving the interactions between bio-molecules (such as DNA, RNA, mi-RNA and proteins). These interactions are analyzed in the form of static networks. Likewise, number of experimental techniques like microarray, RNASeq allows quantification of cellular dynamics and aid...

RIPE (Regulatory network Inference from joint Perturbation and Expression data) is a novel three-step method that integrates both perturbation data and steady state gene expression data in order to estimate a regulatory network. The ripe package is written in R, with additional functionality provided by a MATLAB executable file. The executable file uses a runtime engine called the MATLAB Compiler Runtime (MCR). The executable for different architectures is distributed on this site together...

The VAN package enables an integrative analysis of (i) gene expression data with protein-protein interaction networks or (ii) gene and microRNA expression data with microRNA-gene interaction networks to identify biologically perturbed networks.

This R package can be used to identify TRMs using experimental evidence from a single ChIP-seq experiment. It combines computational predicted transcription factor (TF) binding sites, gene expression and protein-protein interaction (PPI) data and use it to predict TRMs.