Author

Eyal Klang

Icahn School of Medicine at Mount SinaiORCID 0000-0002-4567-3108Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Approach:graph neural network· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:protein structure· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Gideon RechaviiD· 1 shared Ninette AmariglioiD· 1 shared Omri NayshooliD· 1 shared Ortal BareliD· 1 shared Raizy KellermaniD· 1 shared Sharon Paz· 1 shared

Activity by Year

2024-2024 · peak 1/yr

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6 top collaborators · 15 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Gideon RechaviORCID

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1 paper

Recent·Most cited

Mutation Pathogenicity Prediction by a Biology Based Explainable AI Multi-Modal Algorithm

Raizy Kellerman, Omri Nayshool, Ortal Barel, Sharon Paz, Ninette Amariglio, Eyal Klang, Gideon Rechavi

This paper introduces TriVIAI, an explainable AI tool for predicting missense mutation pathogenicity using three modalities, achieving high performance metrics and offering biological insights and explainability.

medRxiv · Jun 5, 2024 · PreprintGenetic & Genomic Medicine