Author

Stéphane Gazut

Commissariat à l'Énergie Atomique et aux Énergies Alternatives

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 4

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Assay:metagenomics· 3 Research Focus:gene regulatory network inference· 2 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Organism:human· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Thomas BrülsiD· 3 shared Vincent ProstiD· 2 shared Bruno Farcy· 1 shared Florian JeanneretiD· 1 shared Olexiy Kyrgyzov· 1 shared Sawsan KanjiD· 1 shared

Activity by Year

2017-2021 · peak 2/yr

Co-Author Collaboration Network

6 top collaborators · 7 mutual co-author links

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3 shared papersBioinformatics

Thomas BrülsORCID

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4 papers

Recent·Most cited

Towards an integrative multi-omics workflow

Florian Jeanneret, Stéphane Gazut

The paper proposes an integrative multi-omics workflow for breast cancer data to improve pathway enrichment analysis by combining sPLS-DA features with Stouffers Z scores method.

bioRxiv · Jul 26, 2021 · PreprintBioinformatics

A zero inflated log-normal model for inference of sparse microbial association networks

Vincent Prost, Stéphane Gazut, Thomas Brüls

This paper introduces a zero-inflated log-normal graphical model for microbial association network inference, showing improved performance on sparse metagenomic data.

PLoS Computational Biology · Jun 18, 2021Peer-reviewedBioinformatics

Binning unassembled short reads based on k-mer covariance using sparse coding

Olexiy Kyrgyzov, Vincent Prost, Stéphane Gazut, Bruno Farcy, Thomas Brüls

This paper introduces a scalable pre-assembly binning method using sparse coding to recover metagenome-assembled genomes from short reads, showing it can recover low-abundance genomes effectively.

GigaScience · Mar 27, 2020Peer-reviewedBioinformatics

Shared Nearest Neighbor clustering in a Locality Sensitive Hashing framework

Sawsan Kanj, Thomas Brüls, Stéphane Gazut

The paper introduces LSH-SNN, a clustering algorithm for high-dimensional sequence data, applied to metagenomics to reconstruct genomes from environmental samples without reference data.

Journal of Computational Biology · Sep 27, 2017Peer-reviewedBioinformatics