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TIGRESS specifications


Unique identifier OMICS_01687
Alternative name Trustful Inference of Gene REgulation using Stability Selection
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages MATLAB
Computer skills Advanced
Stability Stable
Maintained Yes


No version available


  • person_outline Jean-Philippe Vert

Publication for Trustful Inference of Gene REgulation using Stability Selection

TIGRESS citations


Reconstructing directed gene regulatory network by only gene expression data

BMC Genomics
PMCID: 5001240
PMID: 27556418
DOI: 10.1186/s12864-016-2791-2

[…] ed and captured by microarray data, multiple probes designed for the same gene are combined by averaging their expression values. Fig. 6This dataset is then used as the input for ARACNE, CLR, GENIE3, TIGRESS, and CBDN. The results are compared with the true network structure and edge directions from mouse embryonic stem cells experiment. Figure demonstrates the AUC scores for the five methods. CB […]


Data and knowledge based modeling of gene regulatory networks: an update

PMCID: 4817425
PMID: 27047314
DOI: 10.17179/excli2015-168

[…] performance similar to the best-performing community NI. The well-established mutual information NI methods CLR and ARACNE are outperformed by certain LASSO/LARS-based regression methods. The method TIGRESS (Haury et al., 2012[]) combined LARS with a novel feature selection method (‘stability selection’). However, LASSO combined with bootstrapping, which was found to be the best performing indivi […]


Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

BMC Syst Biol
PMCID: 3900469
PMID: 24428926
DOI: 10.1186/1752-0509-8-5

[…] well-known reverse engineering methods. To be specific, in this set of experiments, the DREAM4 multifactorial network 1 with 100 nodes was used, and two well-known inference algorithms (GENIE3 [] and TIGRESS []) were chosen for comparison. Our approach was performed with two fitness functions: (a) the MSE function, and (b), the fitness function described in Part C of the Additional file . The ensu […]


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TIGRESS institution(s)
Centre for Computational Biology, Mines ParisTech, Fontainebleau, France

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