GRNInfer statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.


Citations per year

Citations chart

Popular tool citations

chevron_left Gene regulatory network inference chevron_right
Popular tools chart

Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases


To access compelling stats and trends, optimize your time and resources and pinpoint new correlations, you will need to subscribe to our premium service.


GRNInfer specifications


Unique identifier OMICS_24034
Name GRNInfer
Alternative names Gene Regulatory Network Inference, GNR
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Computer skills Advanced
Version 1.0
Stability Stable
Maintained Yes



Add your version


  • person_outline Luonan Chen <>
  • person_outline Dong Xu <>
  • person_outline Xiang-Sun Zhang <>

Publication for Gene Regulatory Network Inference

GRNInfer in pipeline

PMCID: 2758837
PMID: 19758441
DOI: 10.1186/1752-0509-3-93

[…] regression; cs: control strength; em: expectation-maximization; elu: elutriation; go: gene ontology; tf: transcription factor; tfa: transcription factor activity; nca: network component analysis; grninfer: gene regulatory network inference; rrna: ribosomal rna; utr: untranslated region; rnp: nucleolar ribonucleoprotein; rbps: rna binding proteins; rpm: random periods model., the authors […]

To access a full list of citations, you will need to upgrade to our premium service.

GRNInfer in publications

PMCID: 4991679
PMID: 27432476
DOI: 10.3892/mmr.2016.5527

[…] algorithm. the top 50 genes, including irs1/2, were used as target genes to determine the gene regulatory networks and next the sub-networks of irs1 and irs2 in hcv-huh7 and huh7 cells using gene regulatory network inference tool, an algorithm based on linear programming and the decomposition process. the irs1/2 sub-networks were divided into upstream/downstream groups […]

PMCID: 4439936
PMID: 26000042
DOI: 10.7150/jca.11404

[…] 48 different pearson mutual-positive-correlation epidermal growth factor receptor (egfr_1)-activatory molecular feedback, up- and down-stream network was constructed from 171 overlapping of 366 grninfer and 223 pearson under egfr_1 cc ≥0.25 in high lung adenocarcinoma compared with low human normal adjacent tissues. our identified egfr_1 inside-out upstream activated molecular network […]

PMCID: 4605476
PMID: 24064399
DOI: 10.3233/ACP-130084

[…] compared with lower human normal adjacent tissues from the corresponding comp-stimulated (≥0.25) or inhibited (pearson cc≤−0.25) overlapping molecules of pearson correlation coefficient (cc) and grninfer, respectively. comp complete different activated and inhibited (all no positive correlation, pearson cc< 0.25) mechanisms networks of higher lung adenocarcinoma and lower human normal […]

PMCID: 3576279
PMID: 23426651
DOI: 10.3892/ol.2013.1122

[…] with high expression (fold change ≥2) were identified and computed., amely-activated upstream regulation molecular networks in non-tumor hepatitis/cirrhotic tissues and hcc were constructed by grninfer () and published studies (–), and illustrated by gvedit tool, respectively., the biological processes of amely-activated upstream regulation networks in non-tumor hepatitis/cirrhotic tissues […]

PMCID: 3444843
PMID: 22997493
DOI: 10.1100/2012/428979

[…] go terms from the same activated pthlh go-molecular network of hcc compared with the corresponding activated go-molecular network of no-tumor hepatitis/cirrhotic tissues, and constructed network by grninfer [] and our articles [–] and illustrated by gvedit tool., biological processes and occurrence numbers of the same activated high expression (fold change ≥2) pthlh feedback-mediated cell […]

To access a full list of publications, you will need to upgrade to our premium service.

GRNInfer institution(s)
Department of Electrical Engineering and Electronics, Osaka Sangyo University, Osaka, Japan; Academy of Mathematics and Systems Science, CAS, Beijing, China; Computer Science Department and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA; Institute of Systems Biology, Shanghai University, Shanghai, China
GRNInfer funding source(s)
Supported by project Bioinformatics, Bureau of Basic Science, CAS and by a USDA grant CSREES 2004–25,604-14,708.

GRNInfer reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review GRNInfer