Author

Florent Chatelain

Institut polytechnique de GrenobleORCID 0000-0002-0949-8103Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Dzenis KoçaiD· 2 shared Laurent GuyoniD· 2 shared Rémy Jardillier· 2 shared

Activity by Year

2022-2022 · peak 2/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersBioinformatics

Dzenis KoçaORCID

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2 papers

Recent·Most cited

BioinformaticsGenesPeer-reviewedDec 2, 2022

Optimal microRNA sequencing depth to predict cancer patient survival with random forest and Cox models

Rémy Jardillier, Dzenis Koça, Florent Chatelain, Laurent Guyon

This paper benchmarks the impact of sequencing depth and patient number on survival prediction using miRNA-seq and mRNA-seq with Cox and random survival forest models.

9 citations

bulk RNA-seqstatistical model

𝕏 PostBluesky

BioinformaticsBMC CancerPeer-reviewedOct 5, 2022

Benchmark of lasso-like penalties in the Cox model for TCGA datasets reveal improved performance with pre-filtering and wide differences between cancers

Rémy Jardillier, Dzenis Koça, Florent Chatelain, Laurent Guyon

The paper benchmarks lasso-like penalties in Cox models for TCGA datasets, showing improved performance with pre-filtering and highlighting cancer-specific differences.

36 citations

humanbulk RNA-seq

𝕏 PostBluesky