Section: Software and Platforms

Integrative Biology: (constraint-based) toolbox for network filtering

Participants : Anne Siegel [contact] , Andres Aravena, Jeanne Cambefort [contact] , Guillaume Collet, Damien Eveillard, Sylvain Prigent, Sven Thiele [contact] .

The goal is to offer a toolbox for the reconstruction of networks from genome, literature and large-scale observation data (expression data, metabolomics...) in order to elucidate the main regulators of an observed phenotype. Most of the optimization issues are addressed with Answer Set Programming.

MeMap and MeMerge. We develop a workflow for the Automatic Reconstruction of Metabolic networks (AuReMe). In this workflow, we use heterogeneous sources of data with identifiers from different namespaces. MeMap (Metabolic network Mapping) consists in mapping identifiers from different namespaces to a unified namespace. Then, MeMerge (Metabolic network Merge) merges two metabolic networks previously mapped on the same namespace. [web server] .

meneco [input: draft metabolic network & metabolic profiles. output: metabolic network]. It is a qualitative approach to elaborate the biosynthetic capacities of metabolic networks. In fact, large-scale metabolic networks as well as measured datasets suffer from substantial incompleteness. Moreover, traditional formal approaches to biosynthesis require kinetic information, which is rarely available. Our approach builds upon formal systems for analyzing large-scale metabolic networks. Mapping its principles into Answer Set Programming allows us to address various biologically relevant problems [44] [27] [python package] [web server] .

shogen [input: genome & metabolic network. output : functional regulatory modules]. This software is able to identify genome portions which contain a large density of genes coding for enzymes that regulate successive reactions of metabolic pathways [26] [python package] .

lombarde [input: genome, modules & several gene-expression datasets. output: oriented regulation network]. This tool is useful to enhance key causalities within a regulatory transcriptional network when it is challenged by several environmental perturbations [13] [web server] .

bioquali [input: signed regulation network & one gene-expression dataset. output: consistency-checking and gene-expression prediction]. It is a plugin of the Cytoscape environment. BioQuali analyses regulatory networks and expression datasets by checking a global consistency between the regulatory model and the expression data. It diagnoses a regulatory network searching for the regulations that are not consistent with the expression data, and it outputs a set of genes which predicted expression is decided in order to explain the expression inputed data. It also provides the visualization of this analysis with a friendly environment to encourage users of different disciplines to analyze their regulatory networks [6] [web server] [cytoscape plugin] .

ingranalyze [input: signed regulation network & one gene-expression dataset. output: network repair gene-expression prediction] This tool is an extension to the bioquali tool. It proposes a range of different operations for altering experimental data and/or a biological network in order to re-establish their mutual consistency, an indispensable prerequisite for automated prediction. For accomplishing repair and prediction, we take advantage of the distinguished modeling and reasoning capacities of Answer Set Programming [5] [Python package] [web server] .