Author

D. J. Diaz

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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Biochemistry· 2 Bioengineering· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Approach:graph neural network· 2 Research Focus:protein folding & dynamics· 2 Assay:protein structure· 2 Research Focus:drug response / drug discovery· 1 Assay:protein sequence· 1 Research Focus:sequence-to-function modeling· 1 Approach:statistical model· 1

Frequent Co-Authors

A. D. Ellington· 1 shared A. Dimakis· 1 shared A. J. Ellington· 1 shared A. O. Ellington· 1 shared A. R. Klivans· 1 shared A. V. Kulikova· 1 shared B. Alexander· 1 shared C. Gong· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 12 mutual co-author links

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1 shared paperBioengineering

A. D. Ellington

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Stability Oracle: A Structure-Based Graph-Transformer for Identifying Stabilizing Mutations

D. J. Diaz, C. Gong, J. Ouyang-Zhang, J. M. Loy, J. T. Wells, D. Yang, A. J. Ellington, A. Dimakis, A. R. Klivans

Stability Oracle predicts stabilizing mutations using a structure-based graph-transformer, achieving high accuracy on thermodynamic stability changes.

bioRxiv · May 15, 2023 · PreprintBiochemistry

Two sequence- and two structure-based ML models have learned different aspects of protein biochemistry

A. V. Kulikova, D. J. Diaz, T. Chen, T. J. Cole, A. O. Ellington, C. O. Wilke

The paper compares sequence- and structure-based ML models for predicting protein residue properties, finding they excel at different tasks and that combining them improves accuracy.

bioRxiv · Mar 20, 2023Biochemistry

Deep learning redesign of PETase for practical PET degrading applications

H. Lu, D. J. Diaz, N. J. Czarnecki, C. J. Zhu, W. Kim, D. J. Acosta, B. Alexander, R. Shroff, H. Cole, Y. J. Zhang, N. Lynd, A. D. Ellington, H. S. Alper

This paper uses deep learning to redesign PETase, creating a highly active and stable enzyme for efficient PET degradation and industrial recycling.

bioRxiv · Oct 10, 2021 · PreprintBioengineering