Author

Benjamin P. Danek

National Institutes of HealthORCID 0009-0002-8804-0826Unclaimed 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:benchmarking· 2 Approach:benchmark study· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:multiome· 1

Frequent Co-Authors

Anant DaduiD· 2 shared Andrew SingletoniD· 2 shared Dan VitaleiD· 2 shared Faraz FaghriiD· 2 shared Mary B. MakariousiD· 2 shared Mike A. NallsiD· 2 shared Chelsea X. AlvaradoiD· 1 shared Cory A. WelleriD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Anant DaduORCID

Mutual co-authors in cluster

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2 papers

Recent·Most cited

CARDBiomedBench: A Benchmark for Evaluating Large Language Model Performance in Biomedical Research

Owen Bianchi, Maya Willey, Chelsea X. Alvarado, Benjamin P. Danek, Marzieh Khani, Nicole Kuznetsov, Anant Dadu, Syed Muhammad Tahir Shah, Mathew J. Koretsky, Mary B. Makarious, Cory A. Weller, Kristin S. Levine, Sungwon Kim, Paige Jarreau, Dan Vitale, , Faraz Faghri

CARDBiomedBench evaluates LLM performance in biomedical research using a benchmark focused on neurodegenerative diseases, revealing significant limitations in response quality and safety.

The Lancet Digital Health · Jan 1, 2026Peer-reviewedBioinformatics

Federated Learning for multi-omics: a performance evaluation in Parkinson's disease

Benjamin P. Danek, Mary B. Makarious, Anant Dadu, Dan Vitale, Paul Suhwan Lee, Andrew Singleton, Mike A. Nalls, Jimeng Sun, Faraz Faghri

This study evaluates federated learning models for multi-omics Parkinson's disease prediction, finding they perform comparably to centrally trained models with minor performance differences.

Patterns · Mar 1, 2024Peer-reviewedBioinformatics