89 research outputs found
Phylogenomics of plant genomes: a methodology for genome-wide searches for orthologs in plants
<p>Abstract</p> <p>Background</p> <p>Gene ortholog identification is now a major objective for mining the increasing amount of sequence data generated by complete or partial genome sequencing projects. Comparative and functional genomics urgently need a method for ortholog detection to reduce gene function inference and to aid in the identification of conserved or divergent genetic pathways between several species. As gene functions change during evolution, reconstructing the evolutionary history of genes should be a more accurate way to differentiate orthologs from paralogs. Phylogenomics takes into account phylogenetic information from high-throughput genome annotation and is the most straightforward way to infer orthologs. However, procedures for automatic detection of orthologs are still scarce and suffer from several limitations.</p> <p>Results</p> <p>We developed a procedure for ortholog prediction between <it>Oryza sativa </it>and <it>Arabidopsis thaliana</it>. Firstly, we established an efficient method to cluster <it>A. thaliana </it>and <it>O. sativa </it>full proteomes into gene families. Then, we developed an optimized phylogenomics pipeline for ortholog inference. We validated the full procedure using test sets of orthologs and paralogs to demonstrate that our method outperforms pairwise methods for ortholog predictions.</p> <p>Conclusion</p> <p>Our procedure achieved a high level of accuracy in predicting ortholog and paralog relationships. Phylogenomic predictions for all validated gene families in both species were easily achieved and we can conclude that our methodology outperforms similarly based methods.</p
CollaStar : Interaction collaborative avec des données multidimensionnelles et temporelles
International audienceAlors que la littérature regorge de représentations pour la visualisation de données multidimensionnelles, peu de travaux traitent du contrôle des valeurs de ces données dans le temps. Nous proposons Collastar, une interface permettant à plusieurs utilisateurs de manipuler collaborativement un ensemble de paramètres dynamiques grâce à des techniques d'interaction et de visualisation pertinentes. L'interface est composée d'une représentation en étoile au centre, dédiée à la manipulation collaborative des paramètres dynamiques, et d'autant de fenêtres de visualisation des données (Linear Wall de l'évolution temporelle des paramètres) que d'utilisateurs. Nous utilisons CollaStar pour contrôler un moteur de création de scènes cinématographiques (manipulation des paramètres de caméra) et évaluons notre système qualitativement avec des experts en création cinématographique
Sensitivity analysis in core diagnostics
In the CORTEX project, methods to simulate neutron flux oscillations were enhanced and machine-learning based tools to determine the causes of measured neutron flux oscillations were developed, using the results of simulations as training and validation data. For a selected combination of those methods and tools, several sensitivity analyses were performed to assess their robustness and trustworthiness. The neutron flux oscillations were simulated using the tool CORE SIM+. It calculates the three-dimensional field of the neutron flux oscillations, which can be used to determine the response of neutron detectors at given locations. For the sensitivity analysis, the neutron flux oscillations were assumed to be caused by the vibration of one fuel element. It was investigated how selected input parameters like the core loading pattern, the burn up of the fuel elements, the neutronic core data, the geometry details of the vibrating fuel element, the chosen detectors, and other noise source parameters like the amplitude of the fuel element vibrations, affect the simulated neutron flux oscillations. A three dimensional fully convolutional neural network had been developed and trained during the CORTEX project to determine the cause and location of perturbations causing given measurements of in-core detectors in pressurized water reactors. The robustness of this network was tested by applying it to the simulated detector readings created during the sensitivity analysis
Modelling and simulations of reactor neutron noise induced by mechanical vibrations
Mechanical vibrations of core internals are among the main perturbations that induce oscillations in the neutron flux field, also known as neutron noise. In this work, different simulation models for the study of the influence of the mechanical vibrations of fuel assemblies on the neutron flux in the reactor core have been discussed. These methodologies employ the diffusion approximation, with or without a previous homogenization model, to simulate the neutron noise in the time or the frequency domain. The diffusion-based approach is expected to be less accurate in the vicinity of the vibrating fuel assemblies, but correct when considering distances larger than a few diffusion lengths away from the perturbation. All methodologies provide consistent results and can reproduce typical features of the neutron noise induced by mechanical vibrations of core components. First, FEMFFUSION can perform simulations in both the time and frequency domains. Second, CORE SIM + can be used to study various neutron noise scenarios in realistic three-dimensional reactor configurations. The third methodology is centred on using commercial codes as CASMO-5, SIMULATE-3 and SIMULATE-3K. This methodology allows time domain simulations of the neutron noise induced by different neutron noise sources in a nuclear reactor. Finally, a model for time-dependent geometry is implemented for the code system ATHLET/QUABOX-CUBBOX employing a cross-section-based approach for encoding water gap width variations at the reflector
The phenome analysis of mutant alleles in Leucine-Rich Repeat Receptor-Like Kinase genes in rice reveals new potential targets for stress tolerant cereals
AbstractPlants are constantly exposed to a variety of biotic and abiotic stresses that reduce their fitness and performance. At the molecular level, the perception of extracellular stimuli and the subsequent activation of defense responses require a complex interplay of signaling cascades, in which protein phosphorylation plays a central role. Several studies have shown that some members of the Leucine-Rich Repeat Receptor-Like Kinase (LRR-RLK) family are involved in stress and developmental pathways. We report here a systematic analysis of the role of the members of this gene family by mutant phenotyping in the monocotyledon model plant rice, Oryza sativa. We have then targeted 176 of the ∼320 LRR-RLK genes (55.7%) and genotyped 288 mutant lines. Position of the insertion was confirmed in 128 lines corresponding to 100 LRR-RLK genes (31.6% of the entire family). All mutant lines harboring homozygous insertions have been screened for phenotypes under normal conditions and under various abiotic stresses. Mutant plants have been observed at several stages of growth, from seedlings in Petri dishes to flowering and grain filling under greenhouse conditions. Our results show that 37 of the LRR-RLK rice genes are potential targets for improvement especially in the generation of abiotic stress tolerant cereals
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