Author

O. Chinot

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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Cancer Biology· 2 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Organism:human· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Approach:deep learning· 1 Assay:DNA methylation· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

D. Figarella-Branger· 2 shared E. Tabouret· 2 shared M. Sanson· 2 shared A. A. Bougaev· 1 shared A. Brandes· 1 shared A. Gijtenbeek· 1 shared A. Nowak· 1 shared B. Baumert· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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Curved chords = mutual co-authorship

2 shared papersPharmacology & Toxicology

D. Figarella-Branger

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Combination drug screen targeting glioblastoma core vulnerabilities reveals pharmacological synergisms

J. Ariey-Bonnet, R. Berges, M.-P. Montero, B. Mouysset, P. Piris, K. Muller, G. Pinna, T. W. Failes, G. M. Arndt, N. Baeza-Kallee, C. Colin, O. Chinot, D. Braguer, X. Morelli, N. ANDRE, , E. Pasquier

This study identifies synergistic drug combinations for glioblastoma by screening core vulnerabilities and validating them in preclinical models.

bioRxiv · Dec 14, 2022Pharmacology & Toxicology

DNA methylation and survival differences associated with the type of IDH mutation in 1p/19q non-codeleted astrocytomas

M. Tesileanu, W. Vallentgoed, M. Sanson, W. Taal, P. Clement, W. Wick, A. Brandes, J.-F. Baurain, O. Chinot, H. Wheeler, S. Gill, M. Griffin, L. Rogers, R. Ruda, M. Weller, , van den Bent

The paper shows that IDH mutations other than p.R132H in 1p/19q non-codeleted astrocytomas are linked to higher DNA methylation and better patient survival.

bioRxiv · Dec 10, 2020 · PreprintCancer Biology

An AI-powered blood test to detect cancer using nanoDSF

P. O. Tsvetkov, R. Eyraud, S. Ayache, A. A. Bougaev, S. Malesinski, H. Benazha, S. Gorokhova, C. Buffat, C. Dehais, M. Sanson, F. Bielle, D. Figarella-Branger, O. Chinot, E. Tabouret, F. Devred

This paper presents an AI-powered blood test using nanoDSF to detect cancer with 92% accuracy in glioma patients versus healthy controls.

bioRxiv · Aug 9, 2020Cancer Biology