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Pierre Mahé

Showing results (1-10 of 17) with videos related to

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BMC Bioinformatics|October 19, 2018
Predicting bacterial resistance from whole-genome sequences using k-mers and stability selectionPierre Mahé, Maud Tournoud
Combinatorial Chemistry & High Throughput Screening|May 16, 2009
Virtual screening with support vector machines and structure kernelsPierre Mahé, Jean-Philippe Vert
Methods in Molecular Biology (Clifton, N.J.)|July 22, 2018
MetaVW: Large-Scale Machine Learning for Metagenomics Sequence ClassificationKévin Vervier, Pierre Mahé, Jean-Philippe Vert
Journal of Chemical Information and Modeling|September 26, 2006
The pharmacophore kernel for virtual screening with support vector machinesPierre Mahé, Liva Ralaivola, Véronique Stoven, et al.
Gigascience|October 17, 2020
Interpreting k-mer-based signatures for antibiotic resistance predictionMagali Jaillard, Mattia Palmieri, Alex van Belkum, et al.
Peerj|May 21, 2019
A large scale evaluation of TBProfiler and Mykrobe for antibiotic resistance prediction in <i>Mycobacterium tuberculosis</i>Pierre Mahé, Meriem El Azami, Philippine Barlas, et al.
Journal of Chemical Information and Modeling|July 28, 2005
Graph kernels for molecular structure-activity relationship analysis with support vector machinesPierre Mahé, Nobuhisa Ueda, Tatsuya Akutsu, et al.
Bioinformatics (Oxford, England)|November 22, 2015
Large-scale machine learning for metagenomics sequence classificationKévin Vervier, Pierre Mahé, Maud Tournoud, et al.
Frontiers in Public Health|April 27, 2026
Knowledge, attitudes and practices toward diseases related to water, hygiene and sanitation among inhabitants of informal settlements in French GuianaPierre Mahé, Estelle Thomas, Astrid Van Melle, et al.
Plos Genetics|November 13, 2018
A fast and agnostic method for bacterial genome-wide association studies: Bridging the gap between k-mers and genetic eventsMagali Jaillard, Leandro Lima, Maud Tournoud, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
BMC Bioinformatics|October 19, 2018
Predicting bacterial resistance from whole-genome sequences using k-mers and stability selectionPierre Mahé, Maud Tournoud
Combinatorial Chemistry & High Throughput Screening|May 16, 2009
Virtual screening with support vector machines and structure kernelsPierre Mahé, Jean-Philippe Vert
Methods in Molecular Biology (Clifton, N.J.)|July 22, 2018
MetaVW: Large-Scale Machine Learning for Metagenomics Sequence ClassificationKévin Vervier, Pierre Mahé, Jean-Philippe Vert
Journal of Chemical Information and Modeling|September 26, 2006
The pharmacophore kernel for virtual screening with support vector machinesPierre Mahé, Liva Ralaivola, Véronique Stoven, et al.
Gigascience|October 17, 2020
Interpreting k-mer-based signatures for antibiotic resistance predictionMagali Jaillard, Mattia Palmieri, Alex van Belkum, et al.
Peerj|May 21, 2019
A large scale evaluation of TBProfiler and Mykrobe for antibiotic resistance prediction in <i>Mycobacterium tuberculosis</i>Pierre Mahé, Meriem El Azami, Philippine Barlas, et al.
Journal of Chemical Information and Modeling|July 28, 2005
Graph kernels for molecular structure-activity relationship analysis with support vector machinesPierre Mahé, Nobuhisa Ueda, Tatsuya Akutsu, et al.
Bioinformatics (Oxford, England)|November 22, 2015
Large-scale machine learning for metagenomics sequence classificationKévin Vervier, Pierre Mahé, Maud Tournoud, et al.
Frontiers in Public Health|April 27, 2026
Knowledge, attitudes and practices toward diseases related to water, hygiene and sanitation among inhabitants of informal settlements in French GuianaPierre Mahé, Estelle Thomas, Astrid Van Melle, et al.
Plos Genetics|November 13, 2018
A fast and agnostic method for bacterial genome-wide association studies: Bridging the gap between k-mers and genetic eventsMagali Jaillard, Leandro Lima, Maud Tournoud, et al.
Pageof 2