Author

Sameer D’Costa

University of Wisconsin–MadisonORCID 0009-0007-8143-9574Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:protein design· 2 Assay:protein sequence· 2 Approach:deep learning· 1 Approach:statistical model· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Chase R. FreschliniD· 2 shared Philip A. RomeroiD· 2 shared Anthony GitteriD· 1 shared Arnav SharmaiD· 1 shared Bryce JohnsoniD· 1 shared Emily C. Hinds· 1 shared Hyebin SongiD· 1 shared John Peters· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 26 mutual co-author links

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2 shared papersBioinformatics

Chase R. FreschlinORCID

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2 papers

Recent·Most cited

BioinformaticsNature MethodsPeer-reviewedSep 1, 2025

Biophysics-based protein language models for protein engineering

Sam Gelman, Bryce Johnson, Chase R. Freschlin…·Philip A. Romero

This paper introduces METL, a protein language model that integrates biophysical modeling with machine learning to predict protein properties and design functional variants.

70 citationstop 1%

protein sequencedeep learning

𝕏 PostBluesky

BioinformaticsPLoS Computational BiologyPeer-reviewedMar 1, 2023

Inferring protein fitness landscapes from laboratory evolution experiments

Sameer D’Costa, Emily C. Hinds, Chase R. Freschlin…·Philip A. Romero

This paper develops a statistical learning framework to infer protein fitness landscapes from laboratory evolution data and applies it to DHFR evolution to understand epistasis and design future proteins.

19 citations

protein sequencestatistical model

𝕏 PostBluesky