iFad 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 Differential expression Gene set enrichment analysis Normalization Drug set enrichment analysis Drug sensitivity chevron_right
Popular tools chart

Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases

iFad specifications


Unique identifier OMICS_01959
Name iFad
Alternative name Integrative Factor Analysis for Drug-pathway association inference
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0, GNU General Public License version 2.0
Computer skills Advanced
Version 3.0
Stability Stable
MASS, coda, R(≥2.12.1), Rlab, ROCR
Source code URL https://cran.r-project.org/src/contrib/iFad_3.0.tar.gz
Maintained Yes



Add your version



  • person_outline Haisu Ma <>
  • person_outline Hongyu Zhao <>

Publication for Integrative Factor Analysis for Drug-pathway association inference

iFad in publications

PMCID: 5770056
PMID: 29297378
DOI: 10.1186/s12918-017-0480-7

[…] it build a sparse bayesian factor analysis model to infer pathway responsive for drug treatments []. in order to further improve the performance of the facpad method, another bayesian model named “ifad” is developed to discover the novel drug-pathway associations []. and ma et al. apply the ifad method to analyze gene expression and drug related data from the nci-60 cell lines. the nci-60 cell […]

PMCID: 5564627
PMID: 28624800
DOI: 10.18632/oncotarget.18254

[…] global physiological environment account []. these existing computational methods for identifying drug targets include the gene set enrichment analysis (gsea) method [], the facpad method [], the ifad method [] and the ipad method [], etc. the gsea method has several disadvantages. firstly, for every paired drug-pathway association, calculation must be done once at every turn. secondly, […]

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

iFad institution(s)
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Division of Biostatistics, Yale School of Public Health, New Haven, CT, USA
iFad funding source(s)
Supported by the National Institutes of Health (GM59507) and the NIH R21-GM084008.

iFad reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review iFad