Author

Vafa Bayat

Los Angeles Police DepartmentORCID 0000-0002-1524-0520Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:variant effect prediction· 2 Assay:whole-exome sequencing· 2 Research Focus:benchmarking· 1 Organism:human· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Christopher Edward EisenhartiD· 2 shared Joel MewtoniD· 2 shared Rachel BrickeyiD· 2 shared Brian D. NadoniD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Christopher Edward EisenhartORCID

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2 papers

Recent·Most cited

Genetic & Genomic MedicinemedRxivPreprintFeb 23, 2025

Automating ACMG Variant Classifications With BIAS-2015 v2.0.0: Algorithm Analysis and Benchmark Against the FDA-Approved eRepo Dataset

Christopher Edward Eisenhart, Rachel Brickey, Brian D. Nadon…·Vafa Bayat

BIAS-2015 v2.0.0 automates ACMG variant classification, outperforming InterVar in sensitivity and speed using the FDA-approved eRepo dataset.

DOI 10.1101/2025.02.23.25322737

whole-exome sequencingstatistical model

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Genetic & Genomic MedicinemedRxivPreprintSep 18, 2024

Automating ACMG Variant Classifications Using BIAS-2015: An Algorithm Overview and Benchmark Against the FDA-Approved eRepo Dataset

Christopher Edward Eisenhart, Joel Mewton, Rachel Brickey, Vafa Bayat

The paper introduces BIAS-2015, an open-source algorithm for automating ACMG variant classifications, and benchmarks it against the FDA-approved eRepo dataset.

DOI 10.1101/2024.09.18.24313916

humanwhole-exome sequencing

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