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Fromion, V.

Publications and source records attributed to Fromion, V..

2 recordsLinked to original sources

RBA for eukaryotic cells: foundations and theoretical developments

Resource allocation models were recently identified as new ways to investigate cell design principles. In particular, the Resource Balance Analysis (RBA) framework is the first constraint-based modelling method capable of accurate quantitative predictions of the genome-wide resource allocation. Initially developed and validated on bacteria, the objective of this paper is to provide the mathematical fundations of the extension of the RBA framework to eukaryotic cells. We especially investigate the way to handle the cellular compartments in order to formalize eventually the functioning of organelles. It turns out that the final RBA problem for eukaryotic cells is close to the one of prokaryotic cells from a theoretical point of view. The mathematical properties that were already identified on the prokaryotic RBA framework can be easily transposed to eukaryotic cells. In particular, the eukaryotic RBA problem can be solved easily at the cell scale by Linear Programming. This paves the way to future developments of RBA models for eukaryotic cells.

systems biology

Statistical modeling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to Listeria monocytogenes

Automatic de novo identification of the main regulons of a bacterium from genome and transcriptome data remains a challenge. To address this task, we propose a statistical model of promoter DNA sequences that can use information on exact positions of the transcription start sites and condition-dependent expression profiles. Two main novelties are to allow overlaps between motif occurrences and to incorporate covariates summarising expression profiles (e.g. coordinates in projection spaces or hierarchical clustering trees). All parameters are estimated using a dedicated trans-dimensional Markov chain Monte Carlo algorithm that adjusts, simultaneously, for many motifs and many expression covariates: the width and palindromic properties of the corresponding position-weight matrices, the number of parameters to describe position with respect to the transcription start site, and the choice of relevant expression covariates. A data-set of transcription start sites and expression profiles available for the Listeria monocytogenes is analysed. The results validate the approach and provide a new global view of the transcription regulatory network of this important model food-borne pathogen. A previously unreported motif that may play an important role in the regulation of growth was found in promoter regions of ribosomal protein genes.

bioinformatics