Open Access Methodology article

PTRcombiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps

Gianluca Corrado1, Toma Tebaldi2, Giulio Bertamini1, Fabrizio Costa3, Alessandro Quattrone2, Gabriella Viero24* and Andrea Passerini1*

Author Affiliations

1 Department of Information Engineering and Computer Science (DISI), University of Trento, 38123 Trento, Italy

2 Laboratory of Translational Genomics, Centre for Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy

3 Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, 79110 Freiburg, Germany

4 National Research Council, Institute of Biophysics, 38123 Trento, Italy

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BMC Genomics 2014, 15:304  doi:10.1186/1471-2164-15-304

Published: 23 April 2014



The progress in mapping RNA-protein and RNA-RNA interactions at the transcriptome-wide level paves the way to decipher possible combinatorial patterns embedded in post-transcriptional regulation of gene expression.


Here we propose an innovative computational tool to extract clusters of mRNA trans-acting co-regulators (RNA binding proteins and non-coding RNAs) from pairwise interaction annotations. In addition the tool allows to analyze the binding site similarity of co-regulators belonging to the same cluster, given their positional binding information. The tool has been tested on experimental collections of human and yeast interactions, identifying modules that coordinate functionally related messages.


This tool is an original attempt to uncover combinatorial patterns using all the post-transcriptional interaction data available so far. PTRcombiner is available at webcite.

Post-transcriptional regulation; Boolean matrix factorization; RNA binding protein (RBP); Binding site classification; Kernel machines; miRNA; Translation; CLIP