Bioinformatics | Pharmacogenomics | Pharmacokinetics & Drug Delivery | Drug Discovery & Design | Cancer Therapeutics
iFad: an integrative factor analysis model for drug-pathway association inference
Haisu Ma*, Hongyu Zhao
*Corresponding author: Haisu Ma
Bioinformatics, Yale University, New Haven, CT, USA
F1000Posters 2012, 3: 972 (poster) [English]
Poster [788.96 KB] | Resulting articles
Presented at
International Conference on Intelligent Systems for Molecular Biology (ISMB) 2012,
14 - 16 Jul 2012, A01
A Bayesian sparse factor model for the joint analysis of paired datasets (one is the gene expression dataset and the other is the drug sensitivity profile) was used for taking measurements across a panel of samples, such as, for example, cell lines. Prior knowledge of gene-pathway associations can be easily incorporated into the model to aid the inference of drug-pathway associations.
The model achieves good performance in simulation and real NCI60 data analysis.
No relevant competing interests disclosed.
National Institutes of Health (NIH), R21-GM084008
National Institutes of Health (NIH), GM59507
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