Daniel J. Diaz

发表

A structure-based deep learning framework for protein engineering

Isaac Donnell, Andrew D. Ellington, Raghav Shroff, 2019, bioRxiv.

Deep learning redesign of PETase for practical PET degrading applications

Daniel J. Diaz, H. Alper, A. Ellington, 2021, bioRxiv.

Machine learning-aided engineering of hydrolases for PET depolymerization

Daniel J. Diaz, H. Alper, A. Ellington, 2022, Nature.

Improved Bst DNA Polymerase Variants Derived via a Machine Learning Approach.

Daniel J. Diaz, A. Ellington, R. Shroff, 2021, Biochemistry.

Using machine learning to predict the effects and consequences of mutations in proteins.

Daniel J. Diaz, C. Wilke, A. Ellington, 2023, Current opinion in structural biology.

Learning the local landscape of protein structures with convolutional neural networks

James M. Loy, Daniel J. Diaz, C. Wilke, 2021, Journal of Biological Physics.

Discovery of Novel Gain-of-Function Mutations Guided by Structure-Based Deep Learning.

Isaac Donnell, Andrew D Ellington, Raghav Shroff, 2020, ACS synthetic biology.

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

Adam R. Klivans, James M. Loy, Daniel J. Diaz, 2023, bioRxiv.

Biosensor and machine learning-aided engineering of an amaryllidaceae enzyme

Daniel J. Diaz, H. Alper, Simon d’Oelsnitz, 2024, Nature communications.

Synthetic microbial sensing and biosynthesis of amaryllidaceae alkaloids

Daniel J. Diaz, H. Alper, A. Ellington, 2023, bioRxiv.

HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing

Adam R. Klivans, Daniel J. Diaz, Zhangyang Wang, 2023, ICLR.

Pushing Differential Sensing Further: The Next Steps in Design and Analysis of Bio‐Inspired Cross‐Reactive Arrays

Daniel J. Diaz, E. Anslyn, Simon d’Oelsnitz, 2023, Analysis & Sensing.