The DDG^G-classifier in the functional setting

The Maximum Depth was the first attempt to use data depths instead of multivariate raw data to construct a classification rule. Recently, the DD-classifier has solved several serious limitations of the Maximum Depth classifier but some issues still remain. This paper is devoted to extending the DD-classifier in the following ways: first, to surpass the limitation of the DD-classifier when more than two groups are involved. Second to apply regular classification methods (like $k$NN, linear or quadratic classifiers, recursive partitioning,...) to DD-plots to obtain useful insights through the diagnostics of these methods. And third, to integrate different sources of information (data depths or multivariate functional data) in a unified way in the classification procedure. Besides, as the DD-classifier trick is especially useful in the functional framework, an enhanced revision of several functional data depths is done in the paper. A simulation study and applications to some classical real datasets are also provided showing the power of the new proposal.Comment: 29 pages, 6 figures, 6 tables, Supplemental R Code and Dat

Étude du rôle des effecteurs de type III évolutivement conservés chez deux bactéries colonisatrices du xylème

Xanthomonas campestris pv. campestris (Xcc), l'agent responsable de la pourriture noire chez les Brassicacées, et Ralstonia pseudosolanacearum (Rps), l'agent responsable du flétrissement bactérien chez une large variété d'espèces végétales, sont toutes deux des bactéries dévastatrices s'établissant dans le xylème de leur hôte. Malgré les différences dans leur gamme d'hôtes, leur stratégie infectieuse et leur répertoire d'effecteurs, les souches de référence Xcc8004 et RpsGMI1000 partagent six effecteurs de type III (ET3) définis comme orthologues. Cela offre une excellente opportunité de mener des études comparatives puisqu'il est probable que ces six ET3 ciblent des processus orthologues chez les plantes hôtes, notamment chez Arabidopsis thaliana qui est un hôte commun aux deux pathogènes. Dans une première partie de mon projet de thèse, de potentielles protéines d'Arabidopsis interagissant avec les ET3 de Xcc8004 et RpsGMI1000 ont été identifiées grâce à un criblage par double hybride. Nous avons ainsi pu comparer nos résultats avec des criblages similaires réalisés chez d'autres phytopathogènes afin d'obtenir une vision plus exhaustive de la façon dont les effecteurs interagissent avec le protéome de l'hôte. Cela a permis de générer une base de données interactive intégrant nos résultats ainsi que des données interactomiques Arabidopsis-ET3 déjà publiées : "EffectorK" (www.effectork.org). Dans une deuxième partie du projet, les effets in planta de chacun des ET3 ont été étudiés en générant des lignées transgéniques inductibles d'Arabidopsis. En croisant les résultats de ces deux premières parties, les ET3 candidats les plus prometteurs ont été sélectionnés pour conduire des expériences de caractérisation fonctionnelle, ce qui a constitué la dernière partie de mon travail. Ce projet participe à une meilleure compréhension du rôle biologique des ET3 conservés parmi les bactéries colonisatrices du xylème.Xanthomonas campestris pv. campestris (Xcc), the causal agent of black rot disease on Brassicaceae, and Ralstonia pseudosolanacearum (Rps), the causal agent of bacterial wilt on a wide variety of hosts, are both devastating xylem-colonizing bacteria. Despite their differences in host range, infection strategy and effectome repertoire, reference strains Xcc8004 and RpsGMI1000 share six orthologous type III effectors (T3Es). This provides a valuable opportunity for comparative studies as it is likely that these orthologous T3Es target orthologous processes in the host plants, with focus on Arabidopsis thaliana, common host of both pathogens. In a first part of my PhD project, putative Arabidopsis interactors of Xcc8004 and RpsGMI1000 T3Es were identified by yeast two-hybrid at the effectome-scale. This allowed us to compare our results with similarly screened plant pathogens to acquire a global image of how effectors interfere with the host proteome. This led to the generation of an interactive knowledge database integrating our results with published Arabidopsis-effector interactomic data: "EffectorK" (www.effectork.org). In a second part of the project, the in planta effects of single T3Es were dissected by generating inducible transgenic Arabidopsis lines. Combining results from these two parts, the most promising T3E candidates were selected for further functional characterization, forming the last part of my work. Altogether, this project contributes to a better understanding of the biological role of conserved T3Es among xylem-colonizing bacteria

Elogio del papel. Contra el colonialismo digital

La irrupción de las nuevas tecnologías en el cambio de siglo ha comportado una serie de efectos, en gran parte conocidos por todos, que afectan a diversos ámbitos. Así, no sólo se han redefinido industrias (como las culturales) y oficios (como la profesión periodística), sino que se ha llegado al punto de plantear la necesidad de incorporar las herramientas tecnológicas digitales en el sector educativo y en los procesos de participación política. La digitalización es socialmente percibida como un aspecto positivo per se, donde las crisis de estas industrias y sectores no serían más que la antesala de un cambio de paradigma que acabará por ofrecer más libertad de acción a los ciudadanos.

Advances in functional regression and classification models

Functional data analysis (FDA) has become a very active field of research in the last few years because it appears naturally in most scientific fields: energy (electricity price curves), environment (curves of pollutant levels), chemometrics (spectrometric data), etc. This thesis is a compendium of the following publications: 1) "Statistical computing in functional data analysis: the R package fda.usc" published in the J STAT SOFTW, the core advances of this paper was to propose a common framework for FDA in R. 2) "Predicting seasonal influenza transmission using functional regression models with temporal dependence" published in PLoS ONE proposes an extension of GLS model to functional case. 3) "The DD$^G$--classifier in the functional setting" published in TEST extends the DD-classifier using information derived of the functional depth. 4) "Determining optimum wavelengths for leaf water content estimation from reflectance: A distance correlation approach" published in CHEMOMETR INTELL LAB SYST studies the utility of distance correlation as a method to select impact points in functional regression. 5) "Variable selection in Functional Additive Regression Models", in Comput Stat proposes a variable selection algorithm in the case of mixed predictors (scalar, functional, etc.)

Statistical Computing in Functional Data Analysis: The R Package fda.usc

This paper is devoted to the R package fda.usc which includes some utilities for functional data analysis. This package carries out exploratory and descriptive analysis of functional data analyzing its most important features such as depth measurements or functional outliers detection, among others. The R package fda.usc also includes functions to compute functional regression models, with a scalar response and a functional explanatory data via non-parametric functional regression, basis representation or functional principal components analysis. There are natural extensions such as functional linear models and semi-functional partial linear models, which allow non-functional covariates and factors and make predictions. The functions of this package complement and incorporate the two main references of functional data analysis: The R package fda and the functions implemented by Ferraty and Vieu (2006)S