Éditeur(s) : HAL CCSD IEEE
Résumé : International audience
In this paper, we present an evolutionary approach for extracting a model of flood prediction from hydrological data observed timely on water heights in a river watershed. Since this kind of data recorded by sensors on river basins is highly scarce and hopefully much unbalanced between cases of floods and non-floods, we have adopted the notion of aggregate variables which values are computed as aggregates on raw data. An evolutionary algorithm is involved to allow selecting the best sets - juries of classifiers- of such variables as predictive variables. Two real hydrological data sets are trained and they both show the efficiency of the method compared to traditional solutions for prediction.
IEEE Congress on Evolutionary Computation 2012
Brisbane, Australia

hal-00840739
https://hal.archives-ouvertes.fr/hal-00840739
DOI : 10.1109/CEC.2012.6252897

Résumé : Les travaux de recherche présentés dans ce mémoire s'inscrivent dans la lignée des approches de modélisation hydrologiques prédictives dirigées par les données. Nous avons particulièrement développé leur application sur le contexte difficile des phénomènes de crue éclairs caractéristiques des bassins versants de la région Caraïbe qui pose un dé fi sé.curi taire. En envisageant le problème de la prévision de crues comme un problème d'optimisation combinatoire difficile nous proposons d'utiliser la notion de métaneuristiques, à travers les algorithmes évolutionnaire notamment pour leur capacité à parcourir efficacement de grands espaces de recherche et fi fournir des solutions de bOlIDe qualité en des temps d'exécution raisonnables. Nous avons présenté l'approche de prédiction AV2D : Aggregate Variable Data Driven dom le concept central est la notion de variable agrégée. L'idée sous-jacente à ce concept est de considérer le pouvoir prédictif de nouvelles variables définies comme le résultat de fonctions tatistiques, dites d'agrégation calculées sur de donnée' correspondant à des périodes de temps précédent uo événem nt à prédire. Ces variable sont caractérisées par des ensembles de paramètres correspondant a leur pJ:opriétés. Nous avons imroduitle variables agrégées hydrométéorologiques permettant de répondre au problème de la classification d événements hydrologiques. La complexité du parcours de l'espace de recherche engendré par les paramètres définissant ces variables a été prise en compte grâce à la njse en oeuvre d'un algorithme évolutionnaire particulier dont les composants ont été spécifiquement définis pour ce problème. Nous avons montré, à travers une étude comparative avec d'autres approches de modélisation dirigées par les données, menée sur deux cas d'études de bassins versant caribéens, que l'approche AV2D est particulièrement bien adaptée à leur contexte. Nous étudions par la suite les bénéfices offerts par les approches de modélisation hydrologiques modulaires dirigées par les données, en définissant un procédé de division en sous-processus prenant en compte les caractéristiques paniculières des bassins versants auxquels nous nous intéressons. Nou avons proposé une extension des travaux précédents à travers la définition d'une approche de modélisation modulaire M2D: Spatial Modular Data Driven, consistant à considérer des sous-processus en divisant l'ensemble des exemples à classifier en sous-ensembles correspondant à des comportements hydrologiques homogènes. Nous avons montré à travers une étude comparative avec d autres approches dU'igées par les données mises en oeuvre sur les mêmes sous-ensembles de données que celte approche permet d améliorer les résultats de prédiction particulièrement à coun Lenne. Nous avons enfin proposé la modélisation d un outil de pi
The work presented in this thesis is in the area of data-driven hydrological modeling approaches. We particularly investigared their application on the difficult problem of flash flood phenomena typically observed in Caribbean watersheds. By considering the problem of flood prediction as a combinatorial optimization problem, we propose to use the notion of Oleraheuristics, through evolutionary algorithms, especially for their capacity ta visit effjciently large search space and to provide good solutions in reasonable execution times. We proposed the hydrological prediction approach AV2D: Aggregate Variable Data Driven which central concept is the notion of aggregate variable. The underlying idea of this [concept is to consider the predictive power of new variables defined as the results of statistical functions, called aggregation functions, computed on data corresponding ta time periods before an event ta predict. These variables are characterized by sets of parameters corresponding ta their specifications. We introduced hydro-meteorological aggregate variables allowing ta address the classification problem of hydrological events. We showed through a comparative study on two typical caribbean watersheds, using several common data driven modelling techniques that the AV2D approach is panicul.rly weil fitted ta the studied context. We also study the benefits offered by modulaI' approaches through the definition of the SM2D: Spatial Modular DataDriven approach, consisting in considering sub-processes partly defined by spatial criteria. We showed that the results obtained by the AV2D on these sub-processes allows to increase the performances particularly for short term prediction. Finally we proposed the modelization of a generic control tool for hydro-meteorological prediction systems, H2FCT: Hydro-meteorological Flood Forecasting Control 1'001

http://www.theses.fr/2013AGUY0673/document

Éditeur(s) : HAL CCSD Wiley/Blackwell
Résumé : International audience
Microsatellites are widely used in population genetics to uncover recent evolutionary events. They are typically genotyped using capillary sequencer, which capacity is usually limited to 9, at most 12 loci for each run, and which analysis is a tedious task that is performed by hand. With the rise of next-generation sequencing (NGS), a much larger number of loci and individuals are available from sequencing: for example, on a single run of a GS Junior, 28 loci from 96 individuals are sequenced with a 30X cover. We have developed an algorithm to automatically and efficiently genotype microsatellites from a collection of reads sorted by individual (e.g. specific PCR amplifications of a locus or a collection of reads that encompass a locus of interest). As the sequencing and the PCR amplification introduce artefactual insertions or deletions, the set of reads from a single microsatellite allele shows several length variants. The algorithm infers, without alignment, the true unknown allele(s) of each individual from the observed distributions of microsatellites length of all individuals. MicNeSs, a python implementation of the algorithm, can be used to genotype any microsatellite locus from any organism and has been tested on 454 pyrosequencing data of several loci from fruit flies (a model species) and red deers (a nonmodel species). Without any parallelization, it automatically genotypes 22 loci from 441 individuals in 11 hours on a standard computer. The comparison of MicNeSs inferences to the standard method shows an excellent agreement, with some differences illustrating the pros and cons of both methods.
ISSN: 1755-098X

hal-01544754
https://hal.archives-ouvertes.fr/hal-01544754
DOI : 10.1111/1755-0998.12467

Éditeur(s) : HAL CCSD Oxford University Press (OUP)
Résumé : International audience
Defining homologous genes is important in many evolutionary studies but raises obvious issues. Some of these issues are conceptual and stem from our assumptions of how a gene evolves, others are practical, and depend on the algorithmic decisions implemented in existing software. Therefore, to make progress in the study of homology, both ontological and epistemological questions must be considered. In particular, defining homologous genes cannot be solely addressed under the classic assumptions of strong tree thinking, according to which genes evolve in a strictly tree-like fashion of vertical descent and divergence and the problems of homology detection are primarily methodological. Gene homology could also be considered under a different perspective where genes evolve as ``public goods,'' subjected to various introgressive processes. In this latter case, defining homologous genes becomes a matter of designing models suited to the actual complexity of the data and how such complexity arises, rather than trying to fit genetic data to some a priori tree-like evolutionary model, a practice that inevitably results in the loss of much information. Here we show how important aspects of the problems raised by homology detection methods can be overcome when even more fundamental roots of these problems are addressed by analyzing public goods thinking evolutionary processes through which genes have frequently originated. This kind of thinking acknowledges distinct types of homologs, characterized by distinct patterns, in phylogenetic and nonphylogenetic unrooted or multirooted networks. In addition, we define `` family resemblances'' to include genes that are related through intermediate relatives, thereby placing notions of homology in the broader context of evolutionary relationships. We conclude by presenting some payoffs of adopting such a pluralistic account of homology and family relationship, which expands the scope of evolutionary analyses beyond the traditional, yet relatively narrow focus allowed by a strong tree-thinking view on gene evolution.
ISSN: 0737-4038

hal-01544794
https://hal.archives-ouvertes.fr/hal-01544794
DOI : 10.1093/molbev/mst228

Éditeur(s) : HAL CCSD Public Library of Science
Résumé : International audience
Various types of genome and gene similarity networks along with their characteristics have been increasingly used for retracing different kinds of evolutionary and ecological relationships. Here, we present a new polynomial time algorithm and the corresponding software (BRIDES) to provide characterization of different types of paths existing in evolving (or augmented) similarity networks under the constraint that such paths contain at least one node that was not present in the original network. These different paths are denoted as Breakthroughs , Roadblocks, Impasses, Detours, Equal paths, and Shortcuts. The analysis of their distribution can allow discriminating among different evolutionary hypotheses concerning genomes or genes at hand. Our approach is based on an original application of the popular shortest path Dijkstra's and Yen's algorithms.
ISSN: 1932-6203

Droits : http://creativecommons.org/licenses/by/
hal-01361753
http://hal.upmc.fr/hal-01361753
http://hal.upmc.fr/hal-01361753/document
http://hal.upmc.fr/hal-01361753/file/journal.pone.0161474.PDF
DOI : 10.1371/journal.pone.0161474

Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
The brown algal genus Padina (Dictyotales, Phaeophyceae) is distributed worldwide in tropical and temperate seas. Global species diversity and distribution ranges, however, remain largely unknown. Species-level diversity was reassessed using DNA-based, algorithmic species delineation techniques based on cox3 and rbcL sequence data from 221 specimens collected worldwide. This resulted in estimates ranging from 39 to 61 putative species (ESUs), depending on the technique as well as the locus. We discuss the merits, potential pitfalls, and evolutionary and biogeographic significance of algorithmic species delineation. We unveil patterns whereby ESUs are in all but one case restricted to either the Atlantic or Indo-Pacific Ocean. Within ocean basins we find evidence for the vast majority of ESUs to be confined to a single marine realm. Exceptions, whereby ESUs span up to three realms, are located in the Indo-Pacific Ocean. Patterns of range-restricted species likely arise by repeated founder events and subsequent peripatric speciation, hypothesized to dominate speciation mechanisms for coastal marine organisms in the Indo-Pacific. Using a three-gene (cox3, psaA and rbcL), relaxed molecular clock phylogenetic analysis we estimated divergence times, providing a historical framework to interpret biogeographic patterns.
ISSN: 0022-3646

hal-01545323
https://hal.archives-ouvertes.fr/hal-01545323
DOI : 10.1111/jpy.12027

Éditeur(s) : HAL CCSD springer
Résumé : International audience
In this paper, we address the problem of flood prediction in complex situations. We present an original solution in order to achieve the main goals of accuracy, flexibility and readability. We propose the SM2D modular data driven approach that provides predictive models for each sub-process of a global hydrological process. We show that this solution improves the predictive accuracy regarding a global approach. The originality of our proposition is threefold: (1) the predictive model is defined as a set of aggregate variables that act as classifiers, (2) an evolutionary technique is implemented to find best juries of such classifiers and (3) the flood process complexity problem is addressed by searching for sub-models on sub-processes identified partly by spatial criteria. The solution has proved to perform well on flash flood phenomena of tropical areas known to be hardly predictable. It was indeed successfully applied on a real caribbean river dataset after both preprocessing and preliminary analysis steps presented in the paper.
Lecture notes in computer science
Singapour, Singapore

hal-00878780
https://hal.archives-ouvertes.fr/hal-00878780
DOI : 10.1007/978-3-642-40897-7_13

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
A comprehensive inventory of global biodiversity would be greatly improved by automating methods for species delimitation. The Automatic Barcode Gap Discovery method, the Poisson tree processes algorithm and the Generalized mixed Yule coalescent model have been proposed as means of increasing the rate of biodiversity description using single locus data. We applied these methods to explore the diversity within the Aglaopheniidae, a hydrozoan family with many species widely distributed across tropical and tem perate oceans. Our analyses revealed widespread cryptic diversity in this family, almost half of the morpho species presenting several independent evolutionary lineages, as well as support for cases of synonymy. For two common species of this family, Lytocarpia brevirostris and Macrorhynchia phoenicea, we compared the outputs to clustering analyses based on microsatellite data and to nuclear gene phylo genies. For L. brevirostris, microsatellite data were congruent with results of the species delimitation methods, revealing the existence of two cryptic species with Indo Pacific distribution. For M. phoenicea, all analyses confirmed the presence of two cryptic species within the South Western Indian Ocean. Our study suggests that the diversity of Aglaopheniidae might be much higher than assumed, likely related to low dispersal capacities. Sequence based species delimitation methods seem highly valuable to reveal cryptic diversity in hydrozoans; their application in an integrative framework will be very useful in describing the phyletic diversity of these organisms.
ISSN: 1055-7903

hal-01359407
https://hal.archives-ouvertes.fr/hal-01359407
https://hal.archives-ouvertes.fr/hal-01359407/document
https://hal.archives-ouvertes.fr/hal-01359407/file/Postaire-etal2016MolPhylEvol_sp_delim_hydraires_HAL.pdf
DOI : 10.1016/j.ympev.2016.08.013

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
Algorithms issued from the NonLinear Galerkin method have been used in many situations and with different discretizations for the resolution of evolutionary nonlinear equations. The main idea of these methods is to use a splitting of the solution in order to model the equation. According to the splitting of the solution, a splitting of the equation is obtained. The modeling principle is to freeze terms which have a small time variation. In this work we use wavelet discretizations of the 2-D Burgers equations and compare the results with the hierarchical finite elements method. The numerical tests indicate that wavelets give better results than finite elements
ISSN: 0885-7474

hal-00383423
https://hal.archives-ouvertes.fr/hal-00383423
DOI : 10.1007/s10915-004-4806-4

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
The tropical to warm-temperate marine brown macroalgal genus Lobophora (Dictyotales, Phaeophyceae) recently drew attention because of its striking regional diversity. In this study we reassess Lobophora global species diversity, and species distributions, and explore how historical factors have shaped current diversity patterns. We applied a series of algorithmic species delineation techniques on a global mitochondrial cox3 dataset of 598 specimens, resulting in an estimation of 98–121 species. This diversity by far exceeds traditional diversity estimates based on morphological data. A multi-locus time-calibrated species phylogeny using a relaxed molecular clock, along with DNA-confirmed species distribution data was used to analyse ancestral area distributions, dispersal-vicariance-founder events, and temporal patterns of diversification under different biogeographical models. The origin of Lobophora was estimated in the Upper Cretaceous (−75 to −60 MY), followed by gradual diversification until present. While most speciation events were inferred within marine realms, founder events also played a non-negligible role in Lobophora diversification. The Central Indo-Pacific showed the highest species diversity as a result of higher speciation events in this region. Most Lobophora species have small ranges limited to marine realms. Lobophora probably originated in the Tethys Sea and dispersed repeatedly in the Atlantic (including the Gulf of Mexico) and Pacific Oceans. The formation of the major historical marine barriers (Terminal Tethyan event, Isthmus of Panama, Benguela upwelling) did not act as important vicariance events. Long-distance dispersal presumably represented an important mode of speciation over evolutionary time-scales. The limited geographical ranges of most Lobophora species, however, vouch for the rarity of such events.
ISSN: 1055-7903

hal-01535635
http://hal.upmc.fr/hal-01535635
http://hal.upmc.fr/hal-01535635/document
http://hal.upmc.fr/hal-01535635/file/Vieira_2017_Historical.pdf
DOI : 10.1016/j.ympev.2017.03.007