Characterizing regulatory path motifs in integrated networks using perturbational dataAnagha Joshi
Department of Plant Systems Biology, VIB, Technologiepark 927, Gent, Belgium
Genome Biol 11:R32. 2010
..A case study in Saccharomyces cerevisiae identifies eight regulatory path motifs and demonstrates their biological significance...
Reverse-engineering transcriptional modules from gene expression dataTom Michoel
Department of Plant Systems Biology, VIB, Gent, Belgium
Ann N Y Acad Sci 1158:36-43. 2009
..We show that the inferred probabilistic models extend beyond the dataset used to learn the models...
- Module networks revisited: computational assessment and prioritization of model predictions
Anagha Joshi
Department of Plant Systems Biology, VIB, Ghent University, Technologiepark 927, B 9052 Gent, Belgium
Bioinformatics 25:490-6. 2009
..As time progresses, computational power increases but well-established inference methods often remain locked in their initial suboptimal solution...
- Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks
Tom Michoel
Department of Plant Systems Biology, VIB, Technologiepark 927, B 9052 Gent, Belgium
BMC Syst Biol 3:49. 2009
..To date, there has been no systematic comparison of the relative strengths and weaknesses of both types of methods...
- Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development
Vanessa Vermeirssen
Department of Plant Systems Biology, VIB, B 9052 Ghent, Belgium
Mol Biosyst 5:1817-30. 2009
..In conclusion, through reverse-engineering of C. elegans expression data, we obtained transcription regulatory networks that can provide further insight into metazoan development...
- Module network inference from a cancer gene expression data set identifies microRNA regulated modules
Eric Bonnet
Department of Plant Systems Biology, VIB, Gent, Belgium
PLoS ONE 5:e10162. 2010
..However, defining the place and function of miRNAs in complex regulatory networks is not straightforward. Systems approaches, like the inference of a module network from expression data, can help to achieve this goal...
- Structural and functional organization of RNA regulons in the post-transcriptional regulatory network of yeast
Anagha Joshi
Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust MRC Building Hills Road, Cambridge CB2 0XY, UK
Nucleic Acids Res 39:9108-17. 2011
....
- Validating module network learning algorithms using simulated data
Tom Michoel
Bioinformatics and Evolutionary Genomics, Department of Plant Systems Biology, VIB Ghent University, Ghent, Belgium
BMC Bioinformatics 8:S5. 2007
..Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance...
Analysis of a Gibbs sampler method for model-based clustering of gene expression dataAnagha Joshi
Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Gent, Belgium
Bioinformatics 24:176-83. 2008
..An in-depth analysis can reveal important insights about the performance of the algorithm, the expected quality of the output clusters, and the possibilities for extracting more relevant information out of a particular data set...
