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John B Ingraham

Showing results (1-10 of 9) with videos related to

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Nature Methods|September 26, 2018
Deep generative models of genetic variation capture the effects of mutationsAdam J Riesselman, John B Ingraham, Debora S Marks
Physical Chemistry Chemical Physics : PCCP|October 28, 2020
Generating transition states of isomerization reactions with deep learningLagnajit Pattanaik, John B Ingraham, Colin A Grambow, et al.
Cell|April 19, 2016
3D RNA and Functional Interactions from Evolutionary CouplingsCaleb Weinreb, Adam J Riesselman, John B Ingraham, et al.
Proceedings of the National Academy of Sciences of the United States of America|January 22, 2015
Galactose metabolic genes in yeast respond to a ratio of galactose and glucoseRenan Escalante-Chong, Yonatan Savir, Sean M Carroll, et al.
Nature Biotechnology|January 17, 2017
Mutation effects predicted from sequence co-variationThomas A Hopf, John B Ingraham, Frank J Poelwijk, et al.
Bioinformatics (Oxford, England)|October 11, 2018
The EVcouplings Python framework for coevolutionary sequence analysisThomas A Hopf, Anna G Green, Benjamin Schubert, et al.
Biorxiv : the Preprint Server for Biology|May 22, 2023
Simultaneous enhancement of multiple functional properties using evolution-informed protein designBenjamin Fram, Ian Truebridge, Yang Su, et al.
Nature Communications|June 20, 2024
Simultaneous enhancement of multiple functional properties using evolution-informed protein designBenjamin Fram, Yang Su, Ian Truebridge, et al.
Nature|November 15, 2023
Illuminating protein space with a programmable generative modelJohn B Ingraham, Max Baranov, Zak Costello, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Nature Methods|September 26, 2018
Deep generative models of genetic variation capture the effects of mutationsAdam J Riesselman, John B Ingraham, Debora S Marks
Physical Chemistry Chemical Physics : PCCP|October 28, 2020
Generating transition states of isomerization reactions with deep learningLagnajit Pattanaik, John B Ingraham, Colin A Grambow, et al.
Cell|April 19, 2016
3D RNA and Functional Interactions from Evolutionary CouplingsCaleb Weinreb, Adam J Riesselman, John B Ingraham, et al.
Proceedings of the National Academy of Sciences of the United States of America|January 22, 2015
Galactose metabolic genes in yeast respond to a ratio of galactose and glucoseRenan Escalante-Chong, Yonatan Savir, Sean M Carroll, et al.
Nature Biotechnology|January 17, 2017
Mutation effects predicted from sequence co-variationThomas A Hopf, John B Ingraham, Frank J Poelwijk, et al.
Bioinformatics (Oxford, England)|October 11, 2018
The EVcouplings Python framework for coevolutionary sequence analysisThomas A Hopf, Anna G Green, Benjamin Schubert, et al.
Biorxiv : the Preprint Server for Biology|May 22, 2023
Simultaneous enhancement of multiple functional properties using evolution-informed protein designBenjamin Fram, Ian Truebridge, Yang Su, et al.
Nature Communications|June 20, 2024
Simultaneous enhancement of multiple functional properties using evolution-informed protein designBenjamin Fram, Yang Su, Ian Truebridge, et al.
Nature|November 15, 2023
Illuminating protein space with a programmable generative modelJohn B Ingraham, Max Baranov, Zak Costello, et al.
Pageof 1