Reverse engineering transcriptional regulatory networks from gene expression microarray data using qpgraph
نویسندگان
چکیده
This vignette describes how to use the package qpgraph in order to reverse engineer a transcriptional regulatory network from a particular gene expression microarray data set of Escherichia coli (E. coli). Concretely, the data corresponds to n = 43 experiments of various mutants under oxygen deprivation (Covert et al., 2004). The mutants were designed to monitor the response from E. coli during an oxygen shift in order to target the a priori most relevant part of the transcriptional netwok by using six strains with knockouts of the following key transcriptional regulators in the oxygen response: ∆arcA, ∆appY, ∆fnr, ∆oxyR, ∆soxS and the double knockout ∆arcA∆fnr. To get started, load the following packages:
منابع مشابه
Reverse Engineering Molecular Regulatory Networks from Microarray Data with qp-Graphs
Reverse engineering bioinformatic procedures applied to high-throughput experimental data have become instrumental in generating new hypotheses about molecular regulatory mechanisms. This has been particularly the case for gene expression microarray data, where a large number of statistical and computational methodologies have been developed in order to assist in building network models of tran...
متن کاملUsing Coarse-Grained, Discrete Systems for Data-Driven Inference of Regulatory Gene Networks: Perspectives and Limitations for Reverse Engineering
This contribution gives an initial report of a new project exploring the perspectives and limits of reversely engineering regulatory gene networks from gene expression data. The availability of such data is currently increasing dramatically due to the microarray technology. However, inferring the underlying network from expression data is difficult. We address the reverse engineering problem by...
متن کاملReverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data
Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently a...
متن کاملNonparametric Bayesian inference for perturbed and orthologous gene regulatory networks
MOTIVATION The generation of time series transcriptomic datasets collected under multiple experimental conditions has proven to be a powerful approach for disentangling complex biological processes, allowing for the reverse engineering of gene regulatory networks (GRNs). Most methods for reverse engineering GRNs from multiple datasets assume that each of the time series were generated from netw...
متن کاملFrom Genome to Candidate Cis - Regulatory Networks : A Bioinformatics Approach
Present technological enhancements have resulted in public databases containing data sets of various types: gene expression, protein-DNA interaction and transcription factor (TF) activity data, protein-protein interactions, and genomic sequence and ontology information. The analysis of these large volumes of information holds the promise of uncovering the complex dynamic function of the biochem...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009