1,720,962 research outputs found
Spectre du laplacien sur les formes versus spectre des volumes : le cas des grassmanniennes
No full textSpectre du laplacien sur les formes versus spectre des volumes (le cas des grassmanniennes)
No full textORSAY-PARIS 11-BU Sciences (914712101) / SudocORSAY-PARIS 11-Bib. Maths (914712203) / SudocSudocFranceF
Biogeometric analysis of protein evolution and life history traits
No full textAu-delà de leur rôle fonctionnel dans les cellules, les protéines constituent un matériel important en biologie évolutive parce qu’elles contiennent un signal historique (i.e. phylogénétique) qui peut être utilisé pour retracer leur histoire évolutive, ainsi que celle des organismes. Ce signal est traditionnellement étudié par des méthodes de phylogénie moléculaire basées sur la comparaison des séquences protéiques. L’analyse des structures 3D des protéines a toutefois été proposée comme une alternative intéressante. En effet, les structures évoluent plus lentement que les séquences, offrant ainsi l’accès à un signal phylogénétique plus ancien. Par ailleurs, les séquences protéiques jouent également un rôle clé pour l’étude des processus adaptatifs, comme par exemple l’adaptation à la température environnementale, la salinité ou la pression. La température optimale à laquelle vivent les microorganismes impose des fortes contraintes sur les protéines, notamment sur l’utilisation préférentielle de certains acides aminés. Par conséquent, la composition en acides aminés des protéomes des organismes est liée à leur température optimale de croissance. La température environnementale exerce également des contraintes qui affectent les structures 3D des protéines. Cette thèse aborde l’étude des structures 3D des protéines avec des méthodes issues de l’analyse topologique des données. Nous introduisons des méthodes d’homologie persistante pour analyser les caractéristiques géométriques des structures 3D, ainsi que l’information qu’elles contiennent, notamment concernant leur histoire évolutive (signal phylogénétique) et leur adaptation à la température. Dans un premier temps, nous montrons que l’homologie persistante capture un signal phylogénétique dans les structures 3D. Ensuite, nous définissons une vectorisation des structures 3D pondérée par leurs propriétés physicochimiques et basée sur les descripteurs topologiques de l’homologie persistante. Cette approche permet de raffiner l’estimation des distances évolutives. Nous utilisons ces vectorisations avec des méthodes d’apprentissage automatique pour estimer les températures optimales de croissance d’un groupe majeur d’archées, les Methanococcales. Dans un second temps, nous faisons une analyse spectrale des laplaciens associés aux structures 3D des protéines. En effet, le laplacien capture non seulement les invariants topologiques d’un nuage de point dans son spectre harmonique, comme ceux fournis par l’homologie persistante, mais il saisit également des caractéristiques géométriques liées à la courbure du nuage de point. Nous montrons un théorème de majoration et un théorème de minoration de la courbure d’un espace discret par des valeurs spectrales de son laplacien persistant. Enfin, nous proposons un modèle prédictif d’estimation des températures optimales de croissance des organismes basé sur l’analyse spectrale des structures de leurs protéines.Beyond their functional role in cells, proteins serve as important material in evolutionary biology because they contain a historical (i.e. phylogenetic) signal that can be used to retrace their evolutionary history, as well as that of organisms. This signal is traditionally studied using molecular phylogeny methods based on the comparison of protein sequences. However, the analysis of 3D protein structures has been proposed as an interesting alternative. Indeed, structures evolve more slowly than sequences, offering access to a more ancient phylogenetic signal. On the other hand, protein sequences play also a key role for studying adaptive processes, such as adaptation to environmental temperature, salinity or pressure. The optimal temperature at which microorganisms live imposes very strong constraints on proteins, particularly on the preferential use of certain amino acids. As a result, the amino acid composition of organisms’ proteomes is linked to their optimal growth temperature. Environmental temperature also exerts constraints that affect the 3D structures. This thesis aims to study the 3D structures using methods derived from topological data analysis. We introduce persistent homology methods to analyze the geometric features of 3D structures, as well as the information they contain such as their evolutionary history (phylogenetic signal) and their adaptation to temperature. First, we show that persistent homology captures a phylogenetic signal in 3D structures. We then define a vectorization of 3D structures weighted by their physicochemical properties and based on the topological descriptors of persistent homology. This approach makes it possible to refine the estimation of evolutionary distances. We combine these vectorizations with machine learning methods to estimate the optimal growth temperatures for a major group of archaea, the Methanococcales. Secondly, we carry out a spectral analysis of the Laplacians associated with the 3D structures. The Laplacian captures not only the topological invariants of a point cloud in its harmonic spectrum, such as those provided by persistent homology, but also captures geometric features related to the curvature of the point cloud. We establish lower and upper bounds theorems for the curvature of a discrete space by spectral values of its persistent Laplacian. Finally, we propose a predictive model for estimating the optimal growth temperatures of organisms based on the spectral analysis of their 3D structures
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
New eigenvalue estimates involving Bessel functions
Full text linkGiven a compact Riemannian manifold (Mn, g) with boundary ∂M, we give an estimate for the quotient R ∂M f dµg R M f dµg , where f is a smooth positive function defined on M that satisfies some inequality involving the scalar Laplacian. By the mean value lemma established in [39], we provide a differential inequality for f which, under some curvature assumptions, can be interpreted in terms of Bessel functions. As an application of our main result, a new inequality is given for Dirichlet and Robin Laplacian. Also, a new estimate is established for the eigenvalues of the Dirac operator that involves a positive root of Bessel function besides the scalar curvature. Indepen[1]dently, we extend the Robin Laplacian on functions to differential forms. We prove that this natural extension defines a self-adjoint and elliptic operator whose spectrum is discrete and consists of positive real eigenvalues. In particular, we characterize its first eigenvalue and provide a lower bound of it in terms of Bessel functions
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Riemannian foliations with parallel or harmonic basic forms
Full text linksummary:In this paper, we consider a Riemannian foliation that admits a nontrivial parallel or harmonic basic form. We estimate the norm of the O’Neill tensor in terms of the curvature data of the whole manifold. Some examples are then given
New eigenvalue estimates involving Bessel functions
Full text linkGiven a compact Riemannian manifold (M n , g) with boundary ∂M , we give an estimate for the quotient ∂M f dµ g M f dµ g , where f is a smooth positive function defined on M that satisfies some inequality involving the scalar Laplacian. By the mean value lemma established in [37], we provide a differential inequality for f which, under some curvature assumptions, can be interpreted in terms of Bessel functions. As an application of our main result, a direct proof is given of the Faber-Krahn inequalities for Dirichlet and Robin Laplacian. Also, a new estimate is established for the eigenvalues of the Dirac operator that involves a positive root of Bessel function besides the scalar curvature. Independently, we extend the Robin Laplacian on functions to differential forms. We prove that this natural extension defines a self-adjoint and elliptic operator whose spectrum is discrete and consists of positive real eigenvalues. In particular, we characterize its first eigenvalue and provide a lower bound of it in terms of Bessel functions
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