Reference : Localizing potentially active post-transcriptional regulations in the Ewing's sarcoma...
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/2277
Localizing potentially active post-transcriptional regulations in the Ewing's sarcoma gene regulatory network.
English
Baumuratova, Tatiana mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
Surdez, Didier mailto [Genetics and Biology of Cancers, Institut Curie, Paris, France > Unité 830, INSERM]
Delyon, Bernard mailto [IRMAR, Université de Rennes 1, Rennes, France > UMR 6625, CNRS]
Stoll, Gautier mailto [Service bioinformatique, Institut Curie, Paris, France > Unité 900, INSERM; Service bioinformatique, Mines ParisTech]
Delattre, Olivier mailto [Genetics and Biology of Cancers, Institut Curie, Paris, France > Unité 830, INSERM]
Radulescu, Ovidiu mailto [IRMAR, Université de Rennes 1, Rennes, France > UMR 6625, CNRS, UMR 5235, CNRS, Symbiose project team, INRIA]
Siegel, Anne mailto [Symbiose project team, INRIA, IRISA, Université de Rennes 1, Rennes, France > UMR 6074, CNRS]
2010
BMC Systems Biology
4
146
Yes (verified by ORBilu)
International
1752-0509
England
[en] Cell Line, Tumor ; Gene Expression Profiling ; Gene Regulatory Networks ; Humans ; Insulin-Like Growth Factor Binding Protein 3 ; Insulin-Like Growth Factor Binding Proteins/genetics ; Insulin-Like Growth Factor I/genetics ; Oncogenes/genetics ; Proto-Oncogene Protein c-fli-1/genetics ; Sarcoma, Ewing/genetics ; Software ; Transcription, Genetic
[en] BACKGROUND: A wide range of techniques is now available for analyzing regulatory networks. Nonetheless, most of these techniques fail to interpret large-scale transcriptional data at the post-translational level. RESULTS: We address the question of using large-scale transcriptomic observation of a system perturbation to analyze a regulatory network which contained several types of interactions - transcriptional and post-translational. Our method consisted of post-processing the outputs of an open-source tool named BioQuali - an automatic constraint-based analysis mimicking biologist's local reasoning on a large scale. The post-processing relied on differences in the behavior of the transcriptional and post-translational levels in the network. As a case study, we analyzed a network representation of the genes and proteins controlled by an oncogene in the context of Ewing's sarcoma. The analysis allowed us to pinpoint active interactions specific to this cancer. We also identified the parts of the network which were incomplete and should be submitted for further investigation. CONCLUSIONS: The proposed approach is effective for the qualitative analysis of cancer networks. It allows the integrative use of experimental data of various types in order to identify the specific information that should be considered a priority in the initial - and possibly very large - experimental dataset. Iteratively, new dataset can be introduced into the analysis to improve the network representation and make it more specific.
http://hdl.handle.net/10993/2277

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