Maud Delattre

Learn More
MOTIVATION The spatial conformation of the chromosome has a deep influence on gene regulation and expression. Hi-C technology allows the evaluation of the spatial proximity between any pair of loci along the genome. It results in a data matrix where blocks corresponding to (self-)interacting regions appear. The delimitation of such blocks is critical to(More)
We consider N independent stochastic processes (Xi(t), t ∈ [0, Ti]), i = 1, . . . , N , defined by a stochastic differential equation with drift term depending on a random variable φi. The distribution of the random effect φi depends on unknown parameters which are to be estimated from the continuous observation of the processes Xi. We give the expression(More)
We propose to describe exposure–response relationship of an antiepileptic agent, using mixed hidden Markov modeling methodology, to reveal additional insights in the mode of the drug action which the novel approach offers. Daily seizure frequency data from six clinical studies including patients who received gabapentin were available for the analysis. In(More)
We consider N independent stochastic processes (Xi(t), t ∈ [0, T ]), i = 1, . . . , N , defined by a stochastic differential equation with diffusion coefficients depending linearly on a random variable φi. The distribution of the random effect φi depends on unknown population parameters which are to be estimated from a discrete observation of the processes(More)
Abstract We consider N independent stochastic processes (Xi(t), t ∈ [0, Ti]), i = 1, . . . , N , defined by a stochastic differential equation with drift term depending on a random variable φi. The distribution of the random effect φi is a Gaussian mixture distribution, depending on unknown parameters which are to be estimated from the continuous(More)
— The aim of the present paper is to document the need for adapting the definition of hidden Markov models (HMM) to population studies, which rigorous interpretation typically requires the use of mixed-effects models, as well as for corresponding learning methodologies. In this article, mixed hidden Markov models (MHMM) are introduced through a brief state(More)
BACKGROUND INFORMATION During phagocytosis, neutrophils internalise pathogens in a phagosome and produce reactive oxygen species (ROS) by the NADPH oxidase to kill the pathogen. The cytosolic NADPH oxidase subunits p40(phox), p47(phox), p67(phox) and Rac2 translocate to the phagosomal membrane to participate in enzyme activation. The kinetics of this(More)