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Showing results 461 to 480 on 1266 in total
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On the genetic architecture of Cytoplasmic Incompatibility: inference from phenotypic data
In the absence of a clear understanding of its genetic basis, Cytoplasmic Incompatibility (CI) has so far been conceptualized using a simple toxin-antitoxin model. Under this model, a symbiont's ³compatibility type² is determined by the specific interaction between two components: a modification factor (mod, expressed in sperm) and a rescue factor (resc, expressed in the eggs). Here we confront this model to a well studied, complex and puzzling CI study system: the mosquito Culex pipiens. We show that a more elaborate model is required to account for the observed pattern, including multiple mod and resc genes, and possibly quantitative variation in gene products. We develop such a model and fit its parameters to the data using a parsimony approach. We thereby produce explicit predictions with regards to the genetic architecture of CI; namely, we infer that at least five mod / resc pairs are required to explain the data. These predictions provide a starting point for future genetic and genomic analyses of CI and will hopefully contribute to the decryption of its molecular basis.
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Brown algae, multicellularity and sex
Susana Coelho will present a paper recently published in Nature by an international consortium coordinated by Roscoff on the Ectocarpus genome and the independent evolution of multicellularity in brown algae. Denis Roze will present his theoretical work on deleterious mutations and selection for sex and recombination.
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Mechanistic effect models for ecological risk assessment of chemicals: CREAM and the documentation framework TRACE
Population-level effects of chemicals, for example pesticides, depend not only on exposure and toxicity but also on ecological factors. It is impossible to fully address these factors empirically. Mechanistic effect models, for example ecological models, can solve this problem. They can be used to extrapolate results from single species tests and higher tier tests to the population level and larger scales. Currently, however, there is no common framework that would allow developing such models and assessing their quality in a coherent way. The EU-funded project CREAM ("Mechanistic Effect Models for Ecological Risk Assessments of Chemicals") aims at developing and establishing such a framework. CREAM will not only focus on what Good Modelling Practice is but also on how it can be developed and established. CREAM's central approach will be to use a common framework for documenting the modelling process, dubbed TRACE (Transparent Comprehensive Modelling) documentation. TRACE provides a common structure for organizing and, at the same time, documenting the modelling process on a day-to-day basis. I will demonstrate the use of TRACE using example models. Finally, I will discuss a main further challeng of ecological modelling for chemical risk assessment: the agreement on practical but meaningful population-level endpoints.See the two regional speakers on the SEMOVI web page : http://www.cgmc.univ-lyon1.fr/Semovi/
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Analyse statistique des risques concurrents
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Aspects of dose-response modelling
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L'analyse critique des essais randomisés d'un programme de dépistage : nà propos des derniers essais de dépistage du cancer de la prostate.
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Are bigger brains better?
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"Stirring Tails of Evolution"
One of the most fundamental issues in biology is the nature of evolutionary transitions from single cell organisms to multicellular ones. Not surprisingly for microscopic life in a fluid environment, many of the processes involved are related to transport and locomotion, for efficient exchange of chemical species with the environment is one of the most basic features of life. This is particularly so in the case of flagellated eukaryotes such as green algae, whose members serve as model organisms for the study of transitions to multicellularity. In this talk I will summarize recent theoretical and experimental work addressing a number of interrelated aspects of evolutionary transitions in the Volvocine green algae, which range from unicellular Chlamydomonas to Volvox , with thousands of cells. Phenomena to be discussed include allometry of nutrient uptake, phenotypic plasticity, flagellar synchronization, hydrodynamic bound states, and the dynamics of adaptive phototaxis.For more details, see http://www.cgmc.univ-lyon1.fr/Semovi/13octobre2010.php
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"The mutations responsible for phenotypic evolution : from single casenstudies to general rules"
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Information use, habitat selection and breeding performance in anlandscape of fear
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Systematic protein-genome interaction maps reveal 5 chromatin types in Drosophila.
The local protein composition of chromatin controls important processes such as transcription, replication and DNA repair, yet the diversity of chromatin and its distribution along chromosomes is still poorly characterized.Using DamID in Drosophila Kc cells, we generated high-resolution genome-wide binding maps of 53 chromatin proteins from a wide range of functional categories. For most of those proteins, no binding data was previously available.By constructing a non supervised classifier, we find that there are five principal chromatin types defined by unique yet overlapping combinations of proteins.Two types correspond to Polycomb and HP1-bound regions, respectively. The novel 'BLACK' chromatin type covers half of the genome and induces strong transcriptional repression on inserted transgenes. Remarkably, this chromatin type is devoid of the classic 'heterochromatin' proteins Polycomb and HP1. Thus, our data reveal the existence of a prominent repressive chromatin type that has largely been overlooked.Active genes are associated with one of the other two remaining combinations of proteins. H3K36 methylation is associated with only one of them, yet it was previously thought to mark every transcribed gene. In addition, active genes involved in growth and cell proliferation, and those involved in signal transduction are located in a distinct chromatin types.The five chromatin types modulate the interactions of transcription factors with DNA. We observe that most transcription factors bind their cognate motif only if it sits in the favored chromatin context. Our data rule out a simple exclusion mechanism but support a model whereby synergistic interactions target transcription factors to their binding site.Finally, genomic regions in the 5 chromatin types follow different evolutionary processes. The vast majority of synteny breaks with Drosophila pseudoobscura occurs in only one of the transcriptionally active types. Besides, the speed of evolution of genes located in that chromatin type is higher than for other types.In summary, our integrative approach identifies five major chromatin types, which are defined by unique combinations of proteins and have distinct functional properties.
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The evolution of an informed based dispersal
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La recherche médicale a-t-elle besoin de mathématiques? L'exemple de l'épidémiologie descriptive
L'intervention des mathématiques dans la recherche médicale a eu des fortunes diverses au cours de l'histoire. Si à la fin du 18ième siècle les chercheurs français, comme Gavaret et Louis ont montré la voie en utilisant des outils forgés par Laplace, et enseignés par Poisson à l'école polytechnique pour évaluer l'efficacité des thérapeutiques, l'histoire récente suggère plutôt un divorce entre les deux disciplines dans notre pays, où le malentendu a sans doute son origine dans les diatribes de Claude Bernard contre les statistiques grossières faites par les médecins de son temps. En prenant l'exemple de l'épidémiologie descriptive, souvent considérée comme la moins sophistiquée des disciplines médicales, on peut montrer que la modélisation mathématique y a une importance capitale. Elle permet par exemple de juger objectivement la valeur d'un programme de dépistage ou l'impact des progrès thérapeutiques sur la survie des cancers. Aujourd'hui comme hier cette approche demande une collaboration entre professionnels des deux disciplines partageant leurs points de vue et leurs méthodes et prêts à fonder leurs progrès sur une base de connaissances communes. La disponibilité croissante de ressources informatiques sera de faible utilité si on oublie que les modèles mathématiques reposent d'abord sur la création de concepts adaptés à la discipline à laquelle on envisage de les appliquer.
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Deep divergences of human gene trees and models of human origins
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Les mathématiques à la rescousse de la biodiversité
Pas de résumé
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kml et kml3d: clustérisation des données longitudinales
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Molecular dating of some major events in insect phylogeny
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Fitness consequences of high yolk androgen levels in a wild bird population
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The evolution of useless grandmothers
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Statistical and algorithmic developments for the analysis of SNP/CGH arrays,nwith application to breast cancer data.
Basal-like breast cancers are among the breast cancers with the poorest prognoses and patients do not benefit from any targeted therapy yet. We aim to identify the deregulated signaling pathways using genomic, transcriptomic and proteomic (RPPA) data in order to identify therapeutic targets. In this talk, I will focus on the analysis of SNP and CGH data. More specifically, I will discuss several statistical and algorithmic challenges directly related to their statistical analysis.1) Normalisation One important issue when analyzing SNP profiles is their normalisation. Indeed, especially with tumour profiles, it cannot be assumed that most of the genome is normal and it has been shown that not taking these genomic alterations into account while normalising leads to over-correction. We propose a method to estimate the signal (or copy number) and correct technical artefacts simultaneously.2) Exact and Fast segmentation A CGH profile can be viewed as a succession of segments representing regions in the genome that share the same DNA copy number. Multiple-change-point detection methods constitute a natural framework for their analysis and the detection of breakpoints. However, recovering the optimal position of the breakpoints is not an easy task, especially for large SNP profiles such as Affymetrix SNP 6.0. We propose an algorithm to recover quickly the best segmentation (the maximum likelihood estimate).3) Assessing the quality of a segmentation Assessing the quality of a segmentation and in particular the confidence we have in a particular breakpoint is a difficult problem. We propose algorithms and statistical methods to assess and take into account the quality of possible segmentations.