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John Ingraham
John Ingraham
Generate Biomedicines, Inc
Verified email at csail.mit.edu - Homepage
Title
Cited by
Cited by
Year
Mutation effects predicted from sequence co-variation
TA Hopf, JB Ingraham, FJ Poelwijk, CPI Schärfe, M Springer, C Sander, ...
Nature Biotechnology 35 (2), 128-135, 2017
6972017
Deep generative models of genetic variation capture the effects of mutations
AJ Riesselman, JB Ingraham, DS Marks
Nature Methods 15, 816-822, 2018
6382018
Generative Models for Graph-Based Protein Design
J Ingraham, VK Garg, R Barzilay, T Jaakkola
Neural Information Processing Systems, 2019
5512019
Illuminating protein space with a programmable generative model
JB Ingraham, M Baranov, Z Costello, KW Barber, W Wang, A Ismail, ...
Nature 623 (7989), 1070-1078, 2023
3042023
Defining variant-resistant epitopes targeted by SARS-CoV-2 antibodies: A global consortium study
KM Hastie, H Li, D Bedinger, SL Schendel, SM Dennison, K Li, ...
Science 374 (6566), 472-478, 2021
2942021
Basketball teams as strategic networks
JH Fewell, D Armbruster, J Ingraham, A Petersen, JS Waters
PloS one 7 (11), e47445, 2012
2622012
The EVcouplings Python framework for coevolutionary sequence analysis
TA Hopf, AG Green, B Schubert, S Mersmann, CPI Schärfe, JB Ingraham, ...
Bioinformatics 35 (9), 1582-1584, 2019
2402019
3D RNA and Functional Interactions from Evolutionary Couplings
C Weinreb, AJ Riesselman, JB Ingraham, T Gross, C Sander, DS Marks
Cell 165 (4), 963-975, 2016
1962016
Learning Protein Structure with a Differentiable Simulator
J Ingraham, A Riesselman, C Sander, D Marks
International Conference on Learning Representations, 2019
1682019
Structured States of Disordered Proteins from Genomic Sequences
A Toth-Petroczy, P Palmedo, J Ingraham, TA Hopf, B Berger, C Sander, ...
Cell 167 (1), 158-170. e12, 2016
1522016
Galactose metabolic genes in yeast respond to a ratio of galactose and glucose
R Escalante-Chong, Y Savir, SM Carroll, JB Ingraham, J Wang, CJ Marx, ...
Proceedings of the National Academy of Sciences 112 (5), 1636-1641, 2015
1432015
Cellbox: Interpretable machine learning for perturbation biology with application to the design of cancer combination therapy
B Yuan, C Shen, A Luna, A Korkut, DS Marks, J Ingraham, C Sander
Cell systems 12 (2), 128-140. e4, 2021
1232021
Generating transition states of isomerization reactions with deep learning
L Pattanaik, JB Ingraham, CA Grambow, WH Green
Physical Chemistry Chemical Physics 22 (41), 23618-23626, 2020
562020
Variational Inference for Sparse and Undirected Models
J Ingraham, D Marks
International Conference on Machine Learning, 2017
45*2017
Simultaneous enhancement of multiple functional properties using evolution-informed protein design
B Fram, Y Su, I Truebridge, AJ Riesselman, JB Ingraham, A Passera, ...
Nature Communications 15 (1), 5141, 2024
92024
Antigen Binding Molecules Targeting SARS-CoV-2
G Grigoryan, J Ingraham, CL Leung, RS Federman, RJ Green, V Xue, ...
US Patent App. 18/151,088, 2023
32023
Antigen binding molecules targeting SARS-CoV-2
G Grigoryan, J Ingraham
US Patent 11,987,616, 2024
22024
Probabilistic Models of Structure in Biological Sequences
JB Ingraham
PQDT-Global, 2018
22018
Antigen binding molecules targeting SARS-CoV-2
G Grigoryan, J Ingraham, CL Leung, RS Federman, RJ Green, AH Ramos, ...
US Patent 11,981,725, 2024
2024
Antigen binding molecules targeting sars-cov-2
G GRIGORYAN, J Ingraham, CL Leung, RS FEDERMAN, RJ GREEN, ...
2022
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