TIGRESS statistics

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Citations per year

Number of citations per year for the bioinformatics software tool TIGRESS
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Tool usage distribution map

This map represents all the scientific publications referring to TIGRESS per scientific context
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Associated diseases

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Popular tool citations

chevron_left Gene regulatory network inference Metabolic network analysis chevron_right
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TIGRESS specifications

Information


Unique identifier OMICS_01687
Name TIGRESS
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

Versioning


No version available

Maintainer


  • person_outline Jean-Philippe Vert

Publication for Trustful Inference of Gene REgulation using Stability Selection

TIGRESS citations

 (3)
library_books

Reconstructing directed gene regulatory network by only gene expression data

2016
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 […]

library_books

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

2015
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 […]

library_books

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

2014
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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