Author

J. J. Ferrie

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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Biophysics· 4

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Assay:protein structure· 2 Research Focus:cell-cell communication· 1 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1 Assay:fluorescence / live-cell microscopy· 1 Approach:machine learning (classical)· 1 Research Focus:protein folding & dynamics· 1

Frequent Co-Authors

E. J. Petersson· 2 shared G. M. Dailey· 2 shared R. Tjian· 2 shared X. Darzacq· 2 shared G. Zhang· 1 shared J. P. Karr· 1 shared S. Giannakoulias· 1 shared S. Shringari· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersBiophysics

E. J. Petersson

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4 papers

Recent·Most cited

p300 Is an Obligate Integrator of Combinatorial Transcription Factor Inputs

J. J. Ferrie, J. P. Karr, T. G. Graham, G. M. Dailey, G. Zhang, R. Tjian, X. Darzacq

This study shows p300 requires multiple transcription factor interaction domains for chromatin binding and catalytic regulation, highlighting the necessity of combinatorial TF inputs for coactivator function.

bioRxiv · May 18, 2023Biophysics

Proximity-assisted photoactivation (PAPA): Detecting molecular interactions in live-cell single-molecule imaging

T. G. W. Graham, J. J. Ferrie, G. M. Dailey, R. Tjian, X. Darzacq

This paper introduces PAPA, a method using rhodamine dyes to detect molecular interactions in live-cell single-molecule imaging by reactivating a fluorophore from a dark state when proximal to another.

bioRxiv · Dec 13, 2021Biophysics

Rosetta Custom Score Functions Accurately Predict ΔΔG of Mutations at Protein-Protein Interfaces Using Machine Learning

S. Shringari, S. Giannakoulias, J. J. Ferrie, E. J. Petersson

The paper shows that machine learning reweights Rosetta energy terms to better predict ΔΔG values for protein-protein interface mutations.

bioRxiv · Mar 17, 2020Biophysics

A Unified De Novo Approach for Predicting the Structures of Ordered and Disordered Proteins

J. J. Ferrie, E. J. Petersson

This paper develops PyRosetta-based algorithms for de novo prediction of protein structures, including both ordered and disordered proteins, with accuracy comparable to MD simulations but lower computational demands.

bioRxiv · Jan 30, 2020Biophysics