Section: New Results

Data integration

Participants : Jacques Nicolas, Charles Bettembourg, Jérémie Bourdon, Jeanne Got, Marie Chevallier, Guillaume Collet, Olivier Dameron, Damien Eveillard, Julie Laniau, Anne Siegel.

Extended notions of sign consistency to relate experimental data to signaling and regulatory network topologies. Interaction graphs provide a suitable representation of cellular networks with information flows. Methods based on sign consistency have been shown to be valuable tools to (i) predict qualitative responses, (ii) test the consistency of network topologies and experimental data, and (iii) apply repair operations to the network model suggesting missing or wrong interactions. We present a framework to unify different notions of sign consistency and propose a refined method for data discretization that considers uncertainties in experimental profiles. We furthermore introduce a new constraint to filter undesired model behaviors induced by positive feedback loops. Finally, we generalize the way predictions can be made by the sign consistency approach. This corresponds to an extension of our Bioquali software. [Anne Siegel] [21]

Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach. Our software tool shogen was used to decipher functional roles within a consortium of five mining bacteria through the integration of genomic and metabolic knowledge at genome scale. We first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (i) are close on their respective genomes, (ii) take an active part in metabolic pathways and (iii) whose associated metabolic reactions are also closely connected within metabolic networks. The use of SGS (shogen) pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways. [Damien Eveillard, Anne Siegel] [17]

Optimal Threshold Determination for Interpreting Semantic Similarity and Particularity: Application to the Comparison of Gene Sets and Metabolic Pathways Using GO and ChEBI. We developed a method for determining optimal semantic similarity and particularity thresholds in order to interprete the results of the comparison of ontology terms sets. We applied this method on the GO and ChEBI ontologies. Qualitative analysis using the thresholds on the PPAR multigene family yielded biologically-relevant patterns. [Charles Bettembourg, Olivier Dameron ] [16]

AskOmics : Integration et interrogation de reseaux de regulation genomique et post-genomique. We present AskOmics, an integration and interrogation software using a RDF model and the SPARQL query language. The purpose of this work is to obtain quick answers to biological questions demanding currently hours of manual search in several spreadsheet results files. AskOmics allows biologists to integrate and interrogate their data by themselves without any knowledge about RDF and SPARQL required. [Charles Bettembourg, Olivier Dameron] [30]