Author

Alexandre Colavin

Invitae (United States)ORCID 0000-0002-4996-5378Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:variant effect prediction· 2 Research Focus:benchmarking· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Laure FrésardiD· 2 shared Aasne Karine AarsandiD· 1 shared Aditya Chawla· 1 shared Alexander Wahl· 1 shared Anne‐Florence BitboliD· 1 shared Britt A. JohnsoniD· 1 shared Carlos L. ArayaiD· 1 shared Caroline SchmittiD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Laure FrésardORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

The impact of systematized generation, evaluation, and incorporation of machine learning algorithms for clinical variant classification

Laure Frésard, Flavia M. Facio, Elaine Y. Chen, Alexandre Colavin, Britt A. Johnson, Carlos L. Araya, Toby R. Manders, Alexander Wahl, Hillery C. Metz, Jack Nicoludis, Karen Ouyang, Samskruthi Reddy Padigepati, Yuya Kobayashi, Jason Reuter, Keith Nykamp

The paper develops a machine learning platform to improve variant classification, reducing VUS rates and improving concordance with ClinVar submissions.

medRxiv · Feb 3, 2025 · PreprintGenetic & Genomic Medicine

Systematically testing human HMBS missense variants to reveal mechanism and pathogenic variation

Warren van Loggerenberg, Shahin Sowlati‐Hashjin, Jochen Weile, Rayna Hamilton, Aditya Chawla, Dayag Sheykhkarimli, Marinella Gebbia, Nishka Kishore, Laure Frésard, Sami Mustajoki, Elena Pischik, Elena Di Pierro, Michela Barbaro, Ylva Flodérus, Caroline Schmitt, , Frederick P. Roth

This study systematically tests HMBS missense variants to determine their functional impact and distinguish pathogenic from benign variants.

The American Journal of Human Genetics · Sep 19, 2023Peer-reviewedMolecular Biology

Extracting the phylogenetic dimension of coevolution reveals hidden functional signal

Alexandre Colavin, Esha Atolia, Anne‐Florence Bitbol, Kerwyn Casey Huang

This paper introduces a method to extract the phylogenetic dimension of coevolution, revealing hidden functional signals in proteins and improving structural-contact prediction.

Scientific Reports · Jan 17, 2022Peer-reviewedBioinformatics