Semaine d'Etude Mathématiques et Entreprises 6 : Analyse statistique des défauts en électronique analogique

Nous nous intéressons à des données issues de mesures de tensions sur des circuits électroniques analogiques. Plus précisément, il s'agit de proposer une analyse de courbes représentant l'évolution en fonction du temps des tensions en différents nœuds d'un circuit électronique. Notre objectif est de proposer une analyse automatisée de la qualité des courbes. Plus précisément, nous proposons ici des méthodes statistiques d'analyse de données capable de : -- Identifier d'éventuels patterns dans les courbes (classification), -- Isoler les courbes présentant des "anomalies" (détection de courbes suspectes)

STREAMRHF: Tree-Based Unsupervised Anomaly Detection for Data Streams

International audienceWe present STREAMRHF, an unsupervised anomaly detection algorithm for data streams. Our algorithm builds on some of the ideas of Random Histogram Forest (RHF), a state-of-the-art algorithm for batch unsupervised anomaly detection. STREAMRHF constructs a forest of decision trees, where feature splits are determined according to the kurtosis score of every feature. It irrevocably assigns an anomaly score to data points, as soon as they arrive, by means of an incremental computation of its random trees and the kurtosis scores of the features. This allows efficient online scoring and concept drift detection altogether. Our approach is tree-based which boasts several appealing properties, such as explainability of the results. We conduct an extensive experimental evaluation on multiple datasets from different real-world applications. Our evaluation shows that our streaming algorithm achieves comparable average precision to RHF while outperforming state-of-the-art streaming approaches for unsupervised anomaly detection with furthermore limited computational complexity

Insights into a viral motor : the structure of the HK97 packaging termination assembly

Double-stranded DNA viruses utilise machinery, made of terminase proteins, to package viral DNA into the capsid. For cos bacteriophage, a defined signal, recognised by small terminase, flanks each genome unit. Here we present the first structural data for a cos virus DNA packaging motor, assembled from the bacteriophage HK97 terminase proteins, procapsids encompassing the portal protein, and DNA containing a cos site. The cryo-EM structure is consistent with the packaging termination state adopted after DNA cleavage, with DNA density within the large terminase assembly ending abruptly at the portal protein entrance. Retention of the large terminase complex after cleavage of the short DNA substrate suggests that motor dissociation from the capsid requires headful pressure, in common with pac viruses. Interestingly, the clip domain of the 12-subunit portal protein does not adhere to C12 symmetry, indicating asymmetry induced by binding of the large terminase/DNA. The motor assembly is also highly asymmetric, showing a ring of 5 large terminase monomers, tilted against the portal. Variable degrees of extension between N- and C-terminal domains of individual subunits suggest a mechanism of DNA translocation driven by inter-domain contraction and relaxation

Modular antibodies reveal DNA damage-induced mono-ADP-ribosylation as a second wave of PARP1 signaling

PARP1, an established anti-cancer target that regulates many cellular pathways, including DNA repair signaling, has been intensely studied for decades as a poly(ADP-ribosyl)transferase. Although recent studies have revealed the prevalence of mono-ADP-ribosylation upon DNA damage, it was unknown whether this signal plays an active role in the cell or is just a byproduct of poly-ADP-ribosylation. By engineering SpyTag-based modular antibodies for sensitive and flexible detection of mono-ADP-ribosylation, including fluorescence-based sensors for live-cell imaging, we demonstrate that serine mono-ADP-ribosylation constitutes a second wave of PARP1 signaling shaped by the cellular HPF1/PARP1 ratio. Multilevel chromatin proteomics reveals histone mono-ADP-ribosylation readers, including RNF114, a ubiquitin ligase recruited to DNA lesions through a zinc-finger domain, modulating the DNA damage response and telomere maintenance. Our work provides a technological framework for illuminating ADP-ribosylation in a wide range of applications and biological contexts and establishes mono-ADP-ribosylation by HPF1/PARP1 as an important information carrier for cell signaling. © 2023 The Author(s

Méthodes particulaires et vraisemblances pour l'inférence de modèles d'évolution avec dépendance au contexte

This thesis is devoted to the inference of context-dependent evolutionary models of DNA sequences, and is specifically focused on the RN95+YPR class of stochastic models. This class of models is based on the reinforcement of some substitution rates depending on the local context, which introduces dependence phenomena between sites in the evolution of the DNA sequence. Because of these dependencies, the direct computation of the likelihood of the observed sequences involves high-dimensional matrices, and is usually infeasible. Through encodings specific to the RN95+YpR class, we highlight new spatial dependence structures for these models, which are related to the evolution of DNA sequences throughout their evolutionary history. This enables the use of particle filter algorithms, developed in the context of hidden Markov models, in order to obtain consistent approximations of the likelihood. Another type of approximation of the likelihood, based on composite likelihoods, is also introduced. These approximation methods for the likelihood are implemented in a C++ program. They are applied on simulated data to empirically investigate some of their properties, and on genomic data, especially for comparison of evolutionary modelsCette thèse est consacrée à l'inférence de modèles stochastiques d'évolution de l'ADN avec dépendance au contexte, l'étude portant spécifiquement sur la classe de modèles stochastiques RN95+YpR. Cette classe de modèles repose sur un renforcement des taux d'occurrence de certaines substitutions en fonction du contexte local, ce qui introduit des phénomènes de dépendance dans l'évolution des différents sites de la séquence d'ADN. Du fait de cette dépendance, le calcul direct de la vraisemblance des séquences observées met en jeu des matrices de dimensions importantes, et est en général impraticable. Au moyen d'encodages spécifiques à la classe RN95+YpR, nous mettons en évidence de nouvelles structures de dépendance spatiales pour ces modèles, qui sont associées à l'évolution des séquences d'ADN sur toute leur histoire évolutive. Ceci rend notamment possible l'utilisation de méthodes numériques particulaires, développées dans le cadre des modèles de Markov cachés, afin d'obtenir des approximations consistantes de la vraisemblance recherchée. Un autre type d'approximation de la vraisemblance, basé sur des vraisemblances composites, est également introduit. Ces méthodes d'approximation de la vraisemblance sont implémentées au moyen d'un code en C++. Elles sont mises en œuvre sur des données simulées afin d'étudier empiriquement certaines de leurs propriétés, et sur des données génomiques, notamment à des fins de comparaison de modèles d'évolutio

Sequential Monte Carlo methods and likelihoods for inference of context-dependent evolutionary models

Cette thèse est consacrée à l'inférence de modèles stochastiques d'évolution de l'ADN avec dépendance au contexte, l'étude portant spécifiquement sur la classe de modèles stochastiques RN95+YpR. Cette classe de modèles repose sur un renforcement des taux d'occurrence de certaines substitutions en fonction du contexte local, ce qui introduit des phénomènes de dépendance dans l'évolution des différents sites de la séquence d'ADN. Du fait de cette dépendance, le calcul direct de la vraisemblance des séquences observées met en jeu des matrices de dimensions importantes, et est en général impraticable. Au moyen d'encodages spécifiques à la classe RN95+YpR, nous mettons en évidence de nouvelles structures de dépendance spatiales pour ces modèles, qui sont associées à l'évolution des séquences d'ADN sur toute leur histoire évolutive. Ceci rend notamment possible l'utilisation de méthodes numériques particulaires, développées dans le cadre des modèles de Markov cachés, afin d'obtenir des approximations consistantes de la vraisemblance recherchée. Un autre type d'approximation de la vraisemblance, basé sur des vraisemblances composites, est également introduit. Ces méthodes d'approximation de la vraisemblance sont implémentées au moyen d'un code en C++. Elles sont mises en œuvre sur des données simulées afin d'étudier empiriquement certaines de leurs propriétés, et sur des données génomiques, notamment à des fins de comparaison de modèles d'évolutionThis thesis is devoted to the inference of context-dependent evolutionary models of DNA sequences, and is specifically focused on the RN95+YPR class of stochastic models. This class of models is based on the reinforcement of some substitution rates depending on the local context, which introduces dependence phenomena between sites in the evolution of the DNA sequence. Because of these dependencies, the direct computation of the likelihood of the observed sequences involves high-dimensional matrices, and is usually infeasible. Through encodings specific to the RN95+YpR class, we highlight new spatial dependence structures for these models, which are related to the evolution of DNA sequences throughout their evolutionary history. This enables the use of particle filter algorithms, developed in the context of hidden Markov models, in order to obtain consistent approximations of the likelihood. Another type of approximation of the likelihood, based on composite likelihoods, is also introduced. These approximation methods for the likelihood are implemented in a C++ program. They are applied on simulated data to empirically investigate some of their properties, and on genomic data, especially for comparison of evolutionary model

Interaction du facteur de transcription SRF avec l' ADN (études spectroscopiques des mécanismes de reconnaissance)

PARIS7-Bibliothèque centrale (751132105) / SudocSudocFranceF

A nonlinear model for indirect combustion noise through a compact nozzle

International audienceno abstrac

Capsid expansion of bacteriophage T5 revealed by high resolution cryoelectron microscopy

The large (90-nm) icosahedral capsid of bacteriophage T5 is composed of 775 copies of the major capsid protein (mcp) together with portal, protease, and decoration proteins. Its assembly is a regulated process that involves several intermediates, including a thick-walled round precursor prohead that expands as the viral DNA is packaged to yield a thin-walled and angular mature capsid. We investigated capsid maturation by comparing cryoelectron microscopy (cryo-EM) structures of the prohead, the empty expanded capsid both with and without decoration protein, and the virion capsid at a resolution of 3.8 Å for the latter. We detail the molecular structure of the mcp, its complex pattern of interactions, and their evolution during maturation. The bacteriophage T5 mcp is a variant of the canonical HK97-fold with a high level of plasticity that allows for the precise assembly of a giant macromolecule and the adaptability needed to interact with other proteins and the packaged DNA

Variability in Dispersal Syndromes Is a Key Driver of Metapopulation Dynamics in Experimental Microcosms

International audienceEvolutionary ecology studies have increasingly focused on the impact of intraspecific variability on population processes. However, the role such variation plays in the dynamics of spatially structured populations and how it interacts with environmental changes remains unclear. Here we experimentally quantify the relative importance of intraspecific variability in dispersal-related traits and spatiotemporal variability of environmental conditions for the dynamics of two-patch metapopulations using clonal genotypes of a ciliate in connected microcosms. We demonstrate that in our simple two-patch microcosms, differences among genotypes are at least as important as spatiotemporal variability of resources for metapopulation dynamics. Furthermore, we show that an important proportion of this effect results from variability of dispersal syndromes. These syndromes can therefore be as important for metapopulation dynamics as spatiotemporal variability of environmental conditions. This study demonstrates that intraspecific variability in dispersal syndromes can be key in the functioning of metapopulations facing environmental changes