Author

James M. Loy

The University of Texas at AustinORCID 0000-0001-8519-9482Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Organism:E. coli· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Andrew D. EllingtoniD· 2 shared Daniel J. DiaziD· 2 shared Anastasiya V. KulikovaiD· 1 shared Claus O. WilkeiD· 1 shared Daniel J. AcostaiD· 1 shared Hal S. AlperiD· 1 shared Hannah DoiD· 1 shared James R. HowardiD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersSynthetic Biology

Andrew D. EllingtonORCID

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Author profile →

2 papers

Recent·Most cited

Synthetic microbial sensing and biosynthesis of amaryllidaceae alkaloids

Simon d’Oelsnitz, Daniel J. Diaz, Wantae Kim, Daniel J. Acosta, Tyler L. Dangerfield, Mason W. Schechter, Matthew B. Minus, James R. Howard, Hannah Do, James M. Loy, Hal S. Alper, Yan Zhang, Andrew D. Ellington

The paper develops a biosensor-AI system to engineer E. coli for efficient production of amaryllidaceae alkaloids, achieving improved titer and reduced byproducts.

Nature Communications · Mar 7, 2024Peer-reviewedSynthetic Biology

Learning the local landscape of protein structures with convolutional neural networks

Anastasiya V. Kulikova, Daniel J. Diaz, James M. Loy, Andrew D. Ellington, Claus O. Wilke

This study uses 3D CNNs to predict wild-type amino acids and consensus sequences from local structural context, finding high-confidence predictions correlate with correct outcomes.

Journal of Biological Physics · Nov 9, 2021Peer-reviewedBioinformatics