BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

FRAX(®) Bone Mineral Density Task Force of the 2010 Joint International Society for Clinical Densitometry International Osteoporosis Foundation Position Development Conference.

FRAX(®) is a fracture risk assessment algorithm developed by the World Health Organization in cooperation with other medical organizations and societies. Using easily available clinical information and femoral neck bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA), when available, FRAX(®) is used to predict the 10-year probability of hip fracture and major osteoporotic fracture. These values may be included in country specific guidelines to aid clinicians in determining when fracture risk is sufficiently high that the patient is likely to benefit from pharmacological therapy to reduce that risk. Since the introduction of FRAX(®) into clinical practice, many practical clinical questions have arisen regarding its use. To address such questions, the International Society for Clinical Densitometry (ISCD) and International Osteoporosis Foundations (IOF) assigned task forces to review the best available medical evidence and make recommendations for optimal use of FRAX(®) in clinical practice. Questions were identified and divided into three general categories. A task force was assigned to investigating the medical evidence in each category and developing clinically useful recommendations. The BMD Task Force addressed issues that included the potential use of skeletal sites other than the femoral neck, the use of technologies other than DXA, and the deletion or addition of clinical data for FRAX(®) input. The evidence and recommendations were presented to a panel of experts at the ISCD-IOF FRAX(®) Position Development Conference, resulting in the development of ISCD-IOF Official Positions addressing FRAX(®)-related issues.

Statistics in science and in society: From a state-of-the-art to a new research agenda

Statistics occupies a prominent role in science and citizens' daily life. This article provides a state-of-the-art of the problems associated with statistics in science and in society, structured along the three paradigms defined by Bauer, Allum and Miller (2007). It explores in more detail medicine and public understanding of science on the one hand, and risks and surveys on the other. Statistics has received a good deal of attention; however, very often handled in terms of deficit - either of scientists or of citizens. Many tools have been proposed to improve statistical literacy, the image of and trust in statistics, but with little understanding of their roots, with little coordination among stakeholders and with few assessments of impacts. These deficiencies represent as many new and promising directions in which the PUS research agenda could be expanded.

Information sharing and social network dynamics : a coevolutionary approach

The capacity to interact socially and share information underlies the success of many animal species, humans included. Researchers of many fields have emphasized the evo¬lutionary significance of how patterns of connections between individuals, or the social networks, and learning abilities affect the information obtained by animal societies. To date, studies have focused on the dynamics either of social networks, or of the spread of information. The present work aims to study them together. We make use of mathematical and computational models to study the dynamics of networks, where social learning and information sharing affect the structure of the population the individuals belong to. The number and strength of the relationships between individuals, in turn, impact the accessibility and the diffusion of the shared information. Moreover, we inves¬tigate how different strategies in the evaluation and choice of interacting partners impact the processes of knowledge acquisition and social structure rearrangement. First, we look at how different evaluations of social interactions affect the availability of the information and the network topology. We compare a first case, where individuals evaluate social exchanges by the amount of information that can be shared by the partner, with a second case, where they evaluate interactions by considering their partners' social status. We show that, even if both strategies take into account the knowledge endowments of the partners, they have very different effects on the system. In particular, we find that the first case generally enables individuals to accumulate higher amounts of information, thanks to the more efficient patterns of social connections they are able to build. Then, we study the effects that homophily, or the tendency to interact with similar partners, has on knowledge accumulation and social structure. We compare the case where individuals who know the same information are more likely to learn socially from each other, to the opposite case, where individuals who know different information are instead more likely to learn socially from each other. We find that it is not trivial to claim which strategy is better than the other. Depending on the possibility of forgetting information, the way new social partners can be chosen, and the population size, we delineate the conditions for which each strategy allows accumulating more information, or in a faster way For these conditions, we also discuss the topological characteristics of the resulting social structure, relating them to the information dynamics outcome. In conclusion, this work paves the road for modeling the joint dynamics of the spread of information among individuals and their social interactions. It also provides a formal framework to study jointly the effects of different strategies in the choice of partners on social structure, and how they favor the accumulation of knowledge in the population. - La capacité d'interagir socialement et de partager des informations est à la base de la réussite de nombreuses espèces animales, y compris les humains. Les chercheurs de nombreux domaines ont souligné l'importance évolutive de la façon dont les modes de connexions entre individus, ou réseaux sociaux et les capacités d'apprentissage affectent les informations obtenues par les sociétés animales. À ce jour, les études se sont concentrées sur la dynamique soit des réseaux sociaux, soit de la diffusion de l'information. Le présent travail a pour but de les étudier ensemble. Nous utilisons des modèles mathématiques et informatiques pour étudier la dynamique des réseaux, où l'apprentissage social et le partage d'information affectent la structure de la population à laquelle les individus appartiennent. Le nombre et la solidité des relations entre les individus ont à leurs tours un impact sur l'accessibilité et la diffusion de l'informa¬tion partagée. Par ailleurs, nous étudions comment les différentes stratégies d'évaluation et de choix des partenaires d'interaction ont une incidence sur les processus d'acquisition des connaissances ainsi que le réarrangement de la structure sociale. Tout d'abord, nous examinons comment des évaluations différentes des interactions sociales influent sur la disponibilité de l'information ainsi que sur la topologie du réseau. Nous comparons un premier cas, où les individus évaluent les échanges sociaux par la quantité d'information qui peut être partagée par le partenaire, avec un second cas, où ils évaluent les interactions en tenant compte du statut social de leurs partenaires. Nous montrons que, même si les deux stratégies prennent en compte le montant de connaissances des partenaires, elles ont des effets très différents sur le système. En particulier, nous constatons que le premier cas permet généralement aux individus d'accumuler de plus grandes quantités d'information, grâce à des modèles de connexions sociales plus efficaces qu'ils sont capables de construire. Ensuite, nous étudions les effets que l'homophilie, ou la tendance à interagir avec des partenaires similaires, a sur l'accumulation des connaissances et la structure sociale. Nous comparons le cas où des personnes qui connaissent les mêmes informations sont plus sus¬ceptibles d'apprendre socialement l'une de l'autre, au cas où les individus qui connaissent des informations différentes sont au contraire plus susceptibles d'apprendre socialement l'un de l'autre. Nous constatons qu'il n'est pas trivial de déterminer quelle stratégie est meilleure que l'autre. En fonction de la possibilité d'oublier l'information, la façon dont les nouveaux partenaires sociaux peuvent être choisis, et la taille de la population, nous déterminons les conditions pour lesquelles chaque stratégie permet d'accumuler plus d'in¬formations, ou d'une manière plus rapide. Pour ces conditions, nous discutons également les caractéristiques topologiques de la structure sociale qui en résulte, les reliant au résultat de la dynamique de l'information. En conclusion, ce travail ouvre la route pour la modélisation de la dynamique conjointe de la diffusion de l'information entre les individus et leurs interactions sociales. Il fournit également un cadre formel pour étudier conjointement les effets de différentes stratégies de choix des partenaires sur la structure sociale et comment elles favorisent l'accumulation de connaissances dans la population.

Large-scale DNA sequencing in taxonomy and conservation : a case study with the mayfly family Heptageniidae (Ephemeroptera) in the Alps and Madagascar

Les larves aquatiques d'éphémères (Ephemeroptera) colonisent toutes les eaux douces du monde et sont couramment utilisées comme bio-indicateurs de la qualité de l'eau. Le genre Rhithrogena (Heptageniidae) est le deuxième plus diversifié chez les éphémères, et plusieurs espèces européennes ont une distribution restreinte dans des environnements alpins sensibles. Les espèces de Rhithrogena ont été classées en "groupes d'espèces" faciles à identifier. Cependant, malgré leur importance écologique et en terme de conservation, beaucoup d'espèces présentent des différences morphologiques ambiguës, suggérant que lataxonomie actuelle ne refléterait pas correctement leur diversité évolutive. De plus, aucune information sur leurs relations, leur origine, le taux de spéciation ou les mécanismes ayant provoqué leur remarquable diversification dans les Alpes n'est disponible. Nous avons d'abord examiné le statut spécifique d'environ 50% des espèces européennes de Rhithrogena en utilisant un large échantillonnage de populations alpines incluant 22 localités typiques, ainsi qu'une analyse basée sur le modèle général mixte de Yule et de coalescence (GMYC) appliqué à un gène mitochondrial standard (coxl) et à un gène nucléaire développé spécifiquement pour cette étude. Nous avons observé un regroupement significatif des séquences coxl en 31 espèces potentielles, et nos résultats ont fortement suggéré la présence d'espèces cryptiques et de fractionnements taxonomiques excessifs chez les Rhithrogena. Nos analyses phylogénétiques ont démontré la monophylie de quatre des six groupes d'espèces reconnus présents dans notre échantillonnage. La taxonomie ADN développée dans cette étude pose les bases d'une future révision de ce genre important mais cryptique en Europe. Puis nous avons mené une étude phylogénétique multi-gènes entre les espèces européennes de Rhithrogena. Les données provenant de trois gènes nucléaires et de deux gènes mitochondriaux ont été largement concordantes, et les relations entre les espèces bien résolues au sein de la plupart des groupes d'espèces dans une analyse combinant tous les gènes. En l'absence de points de calibration extérieurs tels que des fossiles, nous avons appliqué à nos données mitochondriales une horloge moléculaire standard pour les insectes, suggérant une origine des Rhithrogena alpins à la limite Oligocène / Miocène. Nos résultats ont montré le rôle prépondérant qu'ont joué les glaciations du quaternaire dans leur diversification, favorisant la spéciation d'au moins la moitié des espèces actuelle dans les Alpes. La biodiversité et le taux d'endémisme à Madagascar, notamment au niveau de la faune des eaux douces, sont parmi les plus extraordinaires et les plus menacés au monde. On pense que beaucoup d'espèces d'éphémères sont restreintes à un seul bassin versant (microendémisme) dans les zones forestières, ce qui les rendrait particulièrement sensibles à la réduction et à la dégradation de leur habitat. Mis à part deux espèces décrites, Afronurus matitensis et Compsoneuria josettae, les Heptageniidae sont pratiquement inconnus à Madagascar. Les deux genres ont une distribution discontinue en Afrique, à Madagascar et en Asie du Sud-Est, et leur taxonomie complexe est régulièrement révisée. L'approche standard pour comprendre leur diversité, leur endémisme et leur origine requerrait un échantillonnage étendu sur plusieurs continents et des années de travaux taxonomiques. Pour accélérer le processus, nous avons utilisé des collections de musées ainsi que des individus fraîchement collectés, et appliqué une approche combinant taxonomie ADN et phylogénie. L'analyses GMYC du gène coxl a délimité 14 espèces potentielles à Madagascar, dont 70% vraisemblablement microendémiques. Une analyse phylogénique incluant des espèces africaines et asiatiques portant sur deux gènes mitochondriaux et quatre gènes nucléaires a montré que les Heptageniidae malgaches sont monophylétiques et groupe frère des Compsoneuria africains. L'existence de cette lignée unique, ainsi qu'un taux élevé de microendémisme, mettent en évidence leur importance en terme de conservation. Nos résultats soulignent également le rôle important que peuvent jouer les collections de musées dans les études moléculaires et en conservation. - Aquatic nymphs of mayflies (Ephemeroptera) colonize all types of freshwaters throughout the world and are extensively used as bio-indicators of water quality. Rhithrogena (Heptageniidae) is the second most species-rich genus of mayflies, and several European species have restricted distributions in sensitive Alpine environments and therefore are of conservation interest. The European Rhithrogena species are arranged into "species groups" that are easily identifiable. However, despite their ecological and conservation importance, ambiguous morphological differences among many species suggest that the current taxonomy may not accurately reflect their evolutionary diversity. Moreover, no information about their relationships, origin, timing of speciation and mechanisms promoting their successful diversification in the Alps is available. We first examined the species status of ca. 50% of European Rhithrogena diversity using a widespread sampling scheme of Alpine species that included 22 type localities, general mixed Yule- coalescent (GMYC) model analysis of one standard mitochondrial (coxl) and one newly developed nuclear marker. We observed significant clustering of coxl into 31 GMYC species, and our results strongly suggest the presence of both cryptic diversity and taxonomic oversplitting in Rhithrogena. Phylogenetic analyses recovered four of the six recognized species groups in our samples as monophyletic. The DNA taxonomy developed here lays the groundwork for a future revision of this important but cryptic genus in Europe. Then we conducted a species-level, multiple-gene phylogenetic study of European Rhithrogena. Data from three nuclear and two mitochondrial loci were broadly congruent, and species-level relationships were well resolved within most species groups in a combined analysis. In the absence of external calibration points like fossils, we applied a standard insect molecular clock hypothesis to our mitochondrial data, suggesting an origin of Alpine Rhithrogena in the Oligocene / Miocene boundary. Our results highlighted the preponderant role that quaternary glaciations played in their diversification, promoting speciation of at least half of the current diversity in the Alps. Madagascar's biodiversity and endemism are among the most extraordinary and endangered in the world. This includes the island's freshwater biodiversity, although detailed knowledge of the diversity, endemism, and biogeographic origin of freshwater invertebrates is lacking. Many mayfly species are thought to be restricted to single river basins (microendemic species) in forested areas, making them particularly sensitive to habitat reduction and degradation. The Heptageniidae are practically unknown in Madagascar except for two described species, Afronurus matitensis and Compsoneuria josettae. Both genera have a disjunct distribution in Africa, Madagascar and Southeast Asia, and a complex taxonomic status still in flux. The standard approach to understanding their diversity, endemism, and origin would require extensive field sampling on several continents and years of taxonomic work. Here we circumvent this using museum collections and freshly collected individuals in a combined approach of DNA taxonomy and phylogeny. The cox/-based GMYC analysis revealed 14 putative species on Madagascar, 70% of which potentially microendemics. A phylogenetic analysis that included African and Asian species and data from two mitochondrial and four nuclear loci indicated the Malagasy Heptageniidae are monophyletic and sister to African Compsoneuria. The observed monophyly and high microendemism highlight their conservation importance. Our results also underline the important role that museum collections can play in molecular studies, especially in critically endangered biodiversity hotspots like Madagascar.

Information and risk management during the first trimester care for pregnant women: Some reflections about the ethical challenges and the legal framework in Switzerland. [L'information et la gestion des risques dans le suivi de la grossesse lors du 1er trimestre : quelques réflexions sur le défi éthique et le cadre légal en Suisse.]

The progress in prenatal medicine raises complex questions with respect to the physician-patient relationship. The physician needs to reconcile medical aspects, ethical principles as well as judicial norms. Already, during the first trimester, the physician has to put into practice the schedule combining for each individual pregnancy physical, laboratory and other appropriate exams. Physicians are under the obligation to inform in a clear and comprehensive way without creating unnecessary anxiety for their patients. Legal requirements include informed consent, the respect for the patient's right to self-determination, and compliance with the Swiss federal law on genetic testing, especially with its articles on prenatal screening and diagnosis. This article discusses the complexity of obstetrical practice when it comes to delivering adequate information within the scope of ethical and legal requirements in Switzerland. L'évolution de la médecine prénatale soulève des enjeux complexes dans la relation médecin-patient. Il s'agit de concilier à la fois les aspects médicaux, les principes éthiques et les normes juridiques. Dès le premier trimestre de la grossesse le médecin doit poser le cadre du suivi et des examens appropriés pour chaque grossesse. Son devoir est d'informer de manière claire et précise sans inquiéter inutilement, en respectant l'exigence légale d'un consentement éclairé et plus largement le droit de la patiente à l'autodétermination ainsi que le cadre de la loi fédérale suisse sur l'analyse génétique humaine dans le domaine du dépistage et du diagnostic prénatal. Cet article discute de la complexité de l'information et de l'application des principes éthiques et légaux dans la pratique obstétricale en Suisse.

T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information and homology extension.

This article introduces a new interface for T-Coffee, a consistency-based multiple sequence alignment program. This interface provides an easy and intuitive access to the most popular functionality of the package. These include the default T-Coffee mode for protein and nucleic acid sequences, the M-Coffee mode that allows combining the output of any other aligners, and template-based modes of T-Coffee that deliver high accuracy alignments while using structural or homology derived templates. These three available template modes are Expresso for the alignment of protein with a known 3D-Structure, R-Coffee to align RNA sequences with conserved secondary structures and PSI-Coffee to accurately align distantly related sequences using homology extension. The new server benefits from recent improvements of the T-Coffee algorithm and can align up to 150 sequences as long as 10,000 residues and is available from both http://www.tcoffee.org and its main mirror http://tcoffee.crg.cat.

Using Pareto optimality to explore the topology and dynamics of the human connectome.

Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial arrangement of network elements, and the resulting network cost and functional performance. An exploration of these interacting factors and driving forces may reveal salient network features that are critically important for shaping and constraining the brain's topological organization and its evolvability. Several studies have pointed to an economic balance between network cost and network efficiency with networks organized in an 'economical' small-world favouring high communication efficiency at a low wiring cost. In this study, we define and explore a network morphospace in order to characterize different aspects of communication efficiency in human brain networks. Using a multi-objective evolutionary approach that approximates a Pareto-optimal set within the morphospace, we investigate the capacity of anatomical brain networks to evolve towards topologies that exhibit optimal information processing features while preserving network cost. This approach allows us to investigate network topologies that emerge under specific selection pressures, thus providing some insight into the selectional forces that may have shaped the network architecture of existing human brains.