Author

Lena Wang

Johns Hopkins University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetics· 1 Genomics· 1

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Organism:human· 2 Research Focus:variant effect prediction· 2 Approach:benchmark study· 1 Assay:DNA methylation· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexis J. BattleiD· 2 shared Eduarda Vaz· 2 shared Rebecca KeeneriD· 2 shared Jake GalviniD· 1 shared Jake Galvin· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 9 mutual co-author links

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2 shared papersGenomics

Alexis J. BattleORCID

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2 papers

Recent·Most cited

Synthetic MPRA perturbation supervision improves variant-effect prediction in sequence-to-function models

Lena Wang, Jake Galvin, Eduarda Vaz, Rebecca Keener, Alexis Battle

This paper improves variant-effect prediction in sequence-to-function models using synthetic MPRA data generated from distilled model predictions.

bioRxiv · Nov 3, 2026 · PreprintGenomics

Fine-tuning sequence to function deep learning models on large-scale proteomic data improves the accuracy of variant effect prediction

Eduarda Vaz, Lena Wang, Jake Galvin, Rebecca Keener, Alexis J. Battle

The paper fine-tunes a sequence-to-function model on large proteomic data to improve variant effect prediction, showing better performance with larger sample sizes and rare variants.

bioRxiv · Sep 26, 2025 · PreprintGenetics