599 citations · 2.7k across the 56 of their papers we have counts for
19 papers · 1 filter
DropLasso: A robust variant of Lasso for single cell RNA-seq data
Beyrem Khalfaoui, Jean-Philippe Vert
Single-cell RNA sequencing (scRNA-seq) is a fast growing approach to measure the genome-wide transcriptome of many individual cells in parallel, but results in noisy data with many…
WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models
Marine Le Morvan, Jean-Philippe Vert
Learning sparse linear models with two-way interactions is desirable in many application domains such as genomics. l1-regularised linear models are popular to estimate sparse model…
Large-scale Machine Learning for Metagenomics Sequence Classification
Kévin Vervier, Pierre Mahé, Maud Tournoud +2
Metagenomics characterizes the taxonomic diversity of microbial communities by sequencing DNA directly from an environmental sample. One of the main challenges in metagenomics data…
The group fused Lasso for multiple change-point detection
Kevin Bleakley, Jean-Philippe Vert
We present the group fused Lasso for detection of multiple change-points shared by a set of co-occurring one-dimensional signals. Change-points are detected by approximating the or…
ProDiGe: PRioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples
Fantine Mordelet, Jean-Philippe Vert
Elucidating the genetic basis of human diseases is a central goal of genetics and molecular biology. While traditional linkage analysis and modern high-throughput techniques often…
The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures
Anne-Claire Haury, Pierre Gestraud, Jean-Philippe Vert
Motivation: Biomarker discovery from high-dimensional data is a crucial problem with enormous applications in biology and medicine. It is also extremely challenging from a statisti…