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A structure-based deep learning framework for protein engineering
Raghav Shroff, Austin W. Cole, Barrett R. Morrow, Daniel J. Diaz, Isaac Donnell, Jimmy Gollihar, Andrew D. Ellington, Ross Thyer
doi: https://doi.org/10.1101/833905
Raghav Shroff
1Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, 78712
Austin W. Cole
1Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, 78712
Barrett R. Morrow
1Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, 78712
Daniel J. Diaz
1Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, 78712
Isaac Donnell
1Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, 78712
Jimmy Gollihar
2US Army Research Laboratories – South, 2506 Speedway, Austin, TX, 78712
Andrew D. Ellington
1Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, 78712
Ross Thyer
1Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, 78712
Article usage
Posted November 08, 2019.
A structure-based deep learning framework for protein engineering
Raghav Shroff, Austin W. Cole, Barrett R. Morrow, Daniel J. Diaz, Isaac Donnell, Jimmy Gollihar, Andrew D. Ellington, Ross Thyer
bioRxiv 833905; doi: https://doi.org/10.1101/833905
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