Author

J. Sulam

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· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Research Focus:drug response / drug discovery· 1 Research Focus:protein design· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

J. A. Ruffolo· 2 shared J. J. Gray· 2 shared C. Guerra· 1 shared S. P. Mahajan· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersBiophysics

J. A. Ruffolo

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2 papers

Recent·Most cited

Antibody structure prediction using interpretable deep learning

J. A. Ruffolo, J. Sulam, J. J. Gray

This paper introduces DeepAb, an interpretable deep learning method for predicting antibody FV structures from sequence, showing improved accuracy and providing insights into residue interactions.

bioRxiv · May 27, 2021Biophysics

Geometric Potentials from Deep Learning Improve Prediction of CDR H3 Loop Structures

J. A. Ruffolo, C. Guerra, S. P. Mahajan, J. Sulam, J. J. Gray

DeepH3 improves CDR H3 loop structure prediction by learning geometric potentials from antibody sequences, outperforming standard Rosetta energy functions in benchmark tests.

bioRxiv · Feb 9, 2020Biophysics