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Baptiste Hennecart

dblp:428/0076 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0000-5945-9359ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
metagenomics
1.012026
StrainMake: reproducible hybrid metagenomics with MAG recovery and strain-level resolution · Bioinform. 2026
Bioinformatics and computational biology › metagenomics
strain-level profiling
1.012026
StrainMake: reproducible hybrid metagenomics with MAG recovery and strain-level resolution · Bioinform. 2026

Methods — techniques the papers use, named apart from their topics

snakemake · 1.0hybrid assembly · 1.0
YearPublicationVenuePosition
2026 StrainMake: reproducible hybrid metagenomics with MAG recovery and strain-level resolution
abstract
SUMMARY: Metagenomic workflows involve complex multi-step analyses, from quality control and assembly to binning, annotation, and strain-level profiling. Few existing metagenomic pipelines achieve the combination of flexibility, reproducibility, and hybrid assembly support within a unified workflow. We present StrainMake, a Snakemake-based workflow for de novo metagenomic analysis from short, long, or hybrid sequencing data. StrainMake integrates widely used tools across all major steps-quality control, assembly, binning, dereplication, taxonomic and functional annotation-while also providing non-redundant gene catalogues, community-scale metabolic models, and strain-level microdiversity metrics. The modular design enables the use of alternative tools, scalable execution on HPC systems, and full reproducibility through Snakemake and Conda. RESULTS: Applied to the CAMI II strain-madness dataset, StrainMake produced high-quality assemblies and metagenome-assembled genomes (MAGs), while enabling strain-resolved comparisons across samples. Hybrid assemblies improved contiguity, whereas short-read assemblies offered faster runtimes, illustrating the workflow's benchmarking capacity. AVAILABILITY AND IMPLEMENTATION: StrainMake is open source and available at https://github.com/UMMISCO/strainmake, together with comprehensive documentation. Generated data are deposited in Zenodo (doi: 10.5281/zenodo.16950162).
Baptiste Hennecart, Eugeni Belda, Raynald de Lahondès, Jean-Daniel Zucker, Edi Prifti
Bioinform.1