Author

Claire Josse

University of LiègeORCID 0000-0003-0315-3718Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Christophe PouletiD· 2 shared Guy JérusalemiD· 2 shared Kristel Van SteeniD· 2 shared Vincent BoursiD· 2 shared Ahmed DebitiD· 1 shared Archana Bhardwaj· 1 shared Benoît CharloteauxiD· 1 shared Benoît Hennuy· 1 shared

Activity by Year

2017-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 26 mutual co-author links

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2 shared papersBioinformatics

Christophe PouletORCID

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3 papers

Recent·Most cited

BioinformaticsBriefings in BioinformaticsPeer-reviewedJun 25, 2025

Assessing Random Forest self-reproducibility for optimal short biomarker signature discovery

Ahmed Debit, Christophe Poulet, Claire Josse…·Kristel Van Steen

The paper introduces AUC hyper-stability scores to improve the selection of Random Forest implementations for stable short biomarker signature discovery.

1 citation

machine learning (classical)benchmarking

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GenomicsScientific ReportsPeer-reviewedJun 30, 2022

Deeper insights into long-term survival heterogeneity of Pancreatic Ductal Adenocarcinoma (PDAC) patients using integrative individual- and group-level transcriptome network analyses

Archana Bhardwaj, Claire Josse, Daniel Van Daele…·Kristel Van Steen

The paper identifies differentially expressed genes and modules associated with long-term survival in PDAC patients using integrative transcriptome analysis.

7 citations

humanbulk RNA-seq

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GenomicsScientific ReportsPeer-reviewedDec 6, 2017

Transcriptome wide analysis of natural antisense transcripts shows their potential role in breast cancer.

Stéphane Wenric, Sonia ElGuendi, Jean‐Hubert Caberg…·Vincent Bours

The paper analyzes natural antisense transcripts (NATs) in breast cancer using RNA sequencing to identify their potential role in gene regulation and survival outcomes.

47 citations

humanbulk RNA-seq

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