Search Results - "Durif, G."

Kernel-based testing for single-cell differential analysis by Ozier-Lafontaine, A, Fourneaux, C, Durif, G, Arsenteva, P, Vallot, C, Gandrillon, O, Gonin-Giraud, S, Michel, B, Picard, F

“…Single-cell technologies offer insights into molecular feature distributions, but comparing them poses challenges. We propose a kernel-testing framework for…”
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Noninvasive prenatal diagnosis of genetic diseases induced by triplet repeat expansion by linked read haplotyping and Bayesian approach by Liautard-Haag, C., Durif, G., VanGoethem, C., Baux, D., Louis, A., Cayrefourcq, L., Lamairia, M., Willems, M., Zordan, C., Dorian, V., Rooryck, C., Goizet, C., Chaussenot, A., Monteil, L., Calvas, P., Miry, C., Favre, R., Le Boette, E., Fradin, M., Roux, A. F., Cossée, M., Koenig, M., Alix-Panabière, C., Guissart, C., Vincent, M. C.

“…The field of noninvasive prenatal diagnosis (NIPD) has undergone significant progress over the last decade. Direct haplotyping has been successfully applied…”
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The Fate of a Polygenic Phenotype Within the Genomic Landscapes of Introgression in the European Seabass Hybrid Zone by Leitwein, Maeva, Durif, Ghislain, Delpuech, Emilie, Gagnaire, Pierre-Alexandre, Ernande, Bruno, Vandeputte, Marc, Vergnet, Alain, Duranton, Maud, Clota, Frederic, Allal, François

“…Abstract Unraveling the evolutionary mechanisms and consequences of hybridization is a major concern in biology. Many studies have documented the interplay…”
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Probabilistic count matrix factorization for single cell expression data analysis by Durif, Ghislain, Modolo, Laurent, Mold, Jeff E, Lambert-Lacroix, Sophie, Picard, Franck

“…Abstract Motivation The development of high-throughput single-cell sequencing technologies now allows the investigation of the population diversity of cellular…”
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High dimensional classification with combined adaptive sparse PLS and logistic regression by Durif, Ghislain, Modolo, Laurent, Michaelsson, Jakob, Mold, Jeff E, Lambert-Lacroix, Sophie, Picard, Franck

“…Abstract Motivation The high dimensionality of genomic data calls for the development of specific classification methodologies, especially to prevent…”
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DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification by Decamps, Clémentine, Arnaud, Alexis, Petitprez, Florent, Ayadi, Mira, Baurès, Aurélia, Armenoult, Lucile, Alcala, N., Arnaud, A., Avila Cobos, F., Batista, Luciana, Batto, A.-F., Blum, Y., Chuffart, F., Cros, J., Decamps, C., Dirian, L., Doncevic, D., Durif, G., Bahena Hernandez, S. Y., Jakobi, M., Jardillier, R., Jeanmougin, M., Jedynak, P., Jumentier, B., Kakoichankava, A., Kondili, Maria, Liu, J., Maie, T., Marécaille, J., Merlevede, J., Meylan, M., Nazarov, P., Newar, K., Nyrén, K., Petitprez, F., Novella Rausell, C., Richard, M., Scherer, M., Sompairac, N., Waury, K., Xie, T., Zacharouli, M.-A., Escalera, Sergio, Guyon, Isabelle, Nicolle, Rémy, Tomasini, Richard, de Reyniès, Aurélien, Cros, Jérôme, Blum, Yuna, Richard, Magali

“…Abstract Background Quantification of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient…”
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Divergent clonal differentiation trajectories establish CD8+ memory T cell heterogeneity during acute viral infections in humans by Mold, Jeff E., Modolo, Laurent, Hård, Joanna, Zamboni, Margherita, Larsson, Anton J.M., Stenudd, Moa, Eriksson, Carl-Johan, Durif, Ghislain, Ståhl, Patrik L., Borgström, Erik, Picelli, Simone, Reinius, Björn, Sandberg, Rickard, Réu, Pedro, Talavera-Lopez, Carlos, Andersson, Björn, Blom, Kim, Sandberg, Johan K., Picard, Franck, Michaëlsson, Jakob, Frisén, Jonas

“…The CD8+ T cell response to an antigen is composed of many T cell clones with unique T cell receptors, together forming a heterogeneous repertoire of effector…”
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High Dimensional Classification with combined Adaptive Sparse PLS and Logistic Regression by Durif, G, Modolo, L, Michaelsson, J, Mold, J. E, Lambert-Lacroix, S, Picard, F

“…Bioinformatics 34, 485-493 (2018) Motivation: The high dimensionality of genomic data calls for the development of specific classification methodologies,…”
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