Output details

Model-based method for transcription factor target identification with limited data

<28> Inferring gene regulatory networks is normally achieved by expensive biological knock outs of certain genes. We show how mechanistic models can be combined with probabilistic models to infer these networks without knock outs. By validating with large scale biological experiments from the Furlong lab at EMBL we showed how our computational approach can significantly outperform wet biology. The work was also released as the ‘Tigre’ software package (2037 distinct downloads in last year) through the Bioconductor framework. The work has 30 cites in Google Scholar. Lawrence and Rattray are the communicating authors.