Inferring gene regulatory networks from temporal expression profiles under time-delay and noise
Computational Biology and Chemistry
Inferring biomolecular interaction networks based on convex optimization
Computational Biology and Chemistry
A mathematical program to refine gene regulatory networks
Discrete Applied Mathematics
Reverse Engineering of Regulatory Relations in Gene Networks by a Probabilistic Approach
WILF '09 Proceedings of the 8th International Workshop on Fuzzy Logic and Applications
An analysis pipeline for the inference of protein-protein interaction networks
International Journal of Data Mining and Bioinformatics
A new multiple regression approach for the construction of genetic regulatory networks
Artificial Intelligence in Medicine
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
CIBB'09 Proceedings of the 6th international conference on Computational intelligence methods for bioinformatics and biostatistics
Inferring stable genetic networks from steady-state data
Automatica (Journal of IFAC)
Tackling the DREAM challenge for gene regulatory networks reverse engineering
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Eigen-Genomic System Dynamic-Pattern Analysis (ESDA): Modeling mRNA Degradation and Self-Regulation
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Supervised inference of gene regulatory networks by linear programming
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Qualitative Reasoning for Biological Network Inference from Systematic Perturbation Experiments
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Reverse engineering of gene regulatory networks from biological data
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Inferring large scale genetic networks with S-system model
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Inferring gene regulatory networks from time-series expressions using random forests ensemble
PRIB'13 Proceedings of the 8th IAPR international conference on Pattern Recognition in Bioinformatics
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Motivation: Time series expression experiments are an increasingly popular method for studying a wide range of biological systems. Here we developed an algorithm that can infer the local network of gene--gene interactions surrounding a gene of interest. This is achieved by a perturbation of the gene of interest and subsequently measuring the gene expression profiles at multiple time points. We applied this algorithm to computer simulated data and to experimental data on a nine gene network in Escherichia coli. Results: In this paper we show that it is possible to recover the gene regulatory network from a time series data of gene expression following a perturbation to the cell. We show this both on simulated data and on a nine gene subnetwork part of the DNA-damage response pathway (SOS pathway) in the bacteria E. coli. Contact: dibernardo@tigem.it Supplementary information: Supplementary data are available at http://dibernado.tigem.it