Author

Chiara Rapisarda

Sanofi (France)ORCID 0000-0002-1867-1385Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:protein structure prediction· 2 Research Focus:drug response / drug discovery· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Approach:graph neural network· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1

Frequent Co-Authors

Ane Miren SalvadoriD· 1 shared Ayman IsmailiD· 1 shared Benjamin BardiauxiD· 1 shared Cécile Capdevila· 1 shared Christelle NonneiD· 1 shared Emily A Hoyt· 1 shared Faith Elaine Yuantiao MoraniD· 1 shared Fiona Maillard· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperNeuroscience

Ane Miren SalvadorORCID

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3 papers

Recent·Most cited

pH-dependent anti-TfR1 NANOBODY(R) molecules deliver efficacious oligonucleotide payloads to muscle and CNS tissues

Emily A Hoyt, Kristof Moonens, Chiara Rapisarda, Ane Miren Salvador, Timothy R. Hammond, Sujay V. Kharade, Ricardo Mondragón-González, Faith Elaine Yuantiao Moran, Shruthi Ramkumar, Jayaprakash Thummapudi, Shan Zhou, Gilles Haussy, Cécile Capdevila, Fiona Maillard, Ayman Ismail, , Nina C. Leksa

This study develops anti-TfR1 NANOBODY(R) molecules that deliver siRNA and ASO payloads to muscle and CNS tissues, achieving significant mRNA knockdown.

bioRxiv · Aug 3, 2026 · PreprintNeuroscience

Finding Antibodies in Cryo-EM densities with CrAI

Vincent Mallet, Chiara Rapisarda, Hervé Minoux, Maks Ovsjanikov

This paper introduces CrAI, a fully automatic method for detecting antibodies in cryo-EM densities, achieving faster and more accurate results than existing methods.

bioRxiv · Sep 27, 2023 · PreprintBioinformatics

Automatic building of protein atomic models from cryo-EM density maps using residue co-evolution

Guillaume Bouvier, Benjamin Bardiaux, Riccardo Pellarin, Chiara Rapisarda, Michaël Nilges

The paper introduces a graph-based method to build atomic protein models from cryo-EM density maps using residue co-evolution data to improve segmentation and sequence assignment.

bioRxiv · Jan 3, 2020 · PreprintBioinformatics