Author

G.F. Hu

University of California, BerkeleyORCID 0009-0006-8705-6411Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Systems Biology· 2

Signature Assays, Organisms & Methods

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Assay:protein sequence· 2 Approach:deep learning· 1 Organism:fungi (other)· 1 Research Focus:gene regulatory network inference· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Angelica Lam· 2 shared Claire J. LeBlanc· 2 shared Marissa A. ZinteliD· 2 shared Max Valentín StalleriD· 2 shared Aaron FultineeriD· 1 shared Aditya Vunnum· 1 shared Emily Chase· 1 shared Giovani Pimentel-Solorio· 1 shared

Activity by Year

2026-2026 · peak 2/yr

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10 top collaborators · 37 mutual co-author links

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2 shared papersSystems Biology

Angelica Lam

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2 papers

Recent·Most cited

Systems BiologyCell SystemsPeer-reviewedAug 17, 2026

Interpretable biophysical neural networks of transcriptional activation domains separate roles of protein abundance and coactivator binding

Claire J. LeBlanc, Pooja Agarwal, Jack Demaray…·Max Valentín Staller

This paper develops interpretable biophysical neural networks to predict transcriptional activation domains from protein sequences, revealing how residue properties influence both activation strength and protein abundance.

1 citation

protein sequencedeep learning

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Systems BiologyPLoS GeneticsPeer-reviewedMar 16, 2026

Evolutionary turnover of key amino acids explains conservation of function without conservation of sequence in transcriptional activation domains

Claire J. LeBlanc, Jordan Stefani, Melvin Soriano…·Max Valentín Staller

The paper shows that function can be conserved in transcriptional activation domains without sequence conservation through evolutionary turnover of key residues.

6 citationstop 4%

fungi (other)protein sequence

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