Author

Édouard Cadieu

Centre National de la Recherche Scientifique

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· 2 Genomics· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 3 Approach:deep learning· 2 Organism:human· 2 Assay:long-read sequencing· 2 Approach:statistical model· 2 Assay:ATAC-seq· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1

Frequent Co-Authors

Thomas DerrieniD· 4 shared Benoît HédaniD· 3 shared Catherine AndréiD· 3 shared Christophe HitteiD· 2 shared Nadine Botherel· 2 shared Victor Le Bars· 2 shared A. N. RusakovichiD· 1 shared Aline Primot· 1 shared

Activity by Year

2018-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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4 shared papersBioinformatics

Thomas DerrienORCID

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Author profile →

5 papers

Recent·Most cited

Benchmarking circRNA Detection Tools from Long-Read Sequencing Using Data-Driven and Flexible Simulation Framework

A. N. Rusakovich, Sébastien Corre, Édouard Cadieu, Rose-Marie Fraboulet, Victor Le Bars, Marie‐Dominique Galibert, Thomas Derrien, Yuna Blum

This paper benchmarks circRNA detection tools using a simulation framework and finds they vary in performance, with limited overlap in detected circRNAs and significant computational efficiency differences.

Peer Community Journal · Mar 25, 2026Peer-reviewedBioinformatics

Facilitating genome annotation using ANNEXA and long-read RNA sequencing

Nicolaï Hoffmann, Aurore Besson, Édouard Cadieu, Matthias Lorthiois, Victor Le Bars, Armel Houël, Christophe Hitte, Catherine André, Benoît Hédan, Thomas Derrien

This study introduces ANNEXA, a pipeline that improves genome annotation using long-read RNA sequencing and deep learning, identifying novel genes and transcripts in human and canine cancer cell lines.

bioRxiv · Apr 16, 2025 · PreprintBioinformatics

Cross-species analysis of melanoma enhancer logic using deep learning

Liesbeth Minnoye, Ibrahim Ihsan Taskiran, David Mauduit, Maurizio Fazio, Linde Van Aerschot, Gert J. Hulselmans, Valerie Christiaens, Samira Makhzami, Monika Heidemarie Seltenhammer, Panagiotis Karras, Aline Primot, Édouard Cadieu, Ellen van Rooijen, Jean‐Christophe Marine, Giorgia Egidy, , Stein Aerts

The paper uses deep learning to analyze enhancer logic across species in melanoma, identifying conserved regulatory complexes and their roles.

Genome Research · Dec 1, 2020Peer-reviewedGenomics

The tree that hides the forest: identification of common predisposing loci in several hematopoietic cancers and several dog breeds.

Benoît Hédan, Édouard Cadieu, Maud Rimbault, Amaury Vaysse, Patrick Devauchelle, Nadine Botherel, Jérôme Abadie, Pascale Quignon, Thomas Derrien, Catherine André

This study identifies common genetic risk loci for hematopoietic cancers in dogs and humans by combining GWAS, sequencing, and imputation across breeds and cancers.

bioRxiv · Jul 23, 2020 · PreprintGenetics

Characterisation and functional predictions of canine long non-coding RNAs

Céline Le Béguec, Valentin Wucher, Laëtitia Lagoutte, Édouard Cadieu, Nadine Botherel, Benoît Hédan, Clotilde De Brito, Anne-Sophie Guillory, Catherine André, Thomas Derrien, Christophe Hitte

The paper characterizes canine lncRNAs across 26 tissues, identifies tissue-specific expression patterns, and links them to transposable elements and conserved human lncRNAs.

Scientific Reports · Sep 3, 2018Peer-reviewedGenomics