Disease-gene discovery by integration of 3D gene expression and transcription factor binding affinities.

Piro RM, Molineris I, Di Cunto F, Eils R, König R (2013) Disease-gene discovery by integration of 3D gene expression and transcription factor binding affinities. Bioinformatics 29(4), 468-475.

Abstract

The computational evaluation of candidate genes for hereditary disorders is a non-trivial task. Several excellent methods for disease-gene prediction have been developed in the past 2 decades, exploiting widely differing data sources to infer disease-relevant functional relationships between candidate genes and disorders. We have shown recently that spatially mapped, i.e. 3D, gene expression data from the mouse brain can be successfully used to prioritize candidate genes for human Mendelian disorders of the central nervous system.

Involved units

Network Modeling

Leibniz-HKI-Authors

Rainer König

Identifier

doi: 10.1093/bioinformatics/bts720

PMID: 23267172