Cécile Bazot

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This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene(More)
In this paper we introduce a new method for analyzing expression patterns from high throughput and complex data such as gene expression microarrays. These microarrays are collected under different conditions such as time, phenotype and treatment. The proposed method uses a Bayesian matrix decomposition , called Bayesian linear unmixing (BLU), to extract a(More)
– Cet article présente un modèle Bayésien hiérarchique d'analyse factorielle, appliqué à des données génétiques. Chaque échantillon observé est la combinaison d'un certain nombre de signatures génétiques (ou facteurs) parmi une bibliothèque de facteurs, suivant un modèle de mélange linéaire. La particularité de la méthode proposée est de prendre en compte(More)
In this additional file, the directed acyclic graph (DAG) of the model and the flowchart of the proposed uBLU algorithm are provided. More results on synthetic datasets are presented to validate the proposed Bayesian algorithm. 1 Summary of the model We consider the model described in the paper (see Section " Methods ") We propose to project the factors m r(More)
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