John Ingraham
John Ingraham
FVL56, 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
2122017
Basketball teams as strategic networks
JH Fewell, D Armbruster, J Ingraham, A Petersen, JS Waters
PloS one 7 (11), e47445, 2012
1522012
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
1092016
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
992016
Deep generative models of genetic variation capture the effects of mutations
AJ Riesselman, JB Ingraham, DS Marks
Nature Methods 15, 816-822, 2018
862018
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
842015
Learning Protein Structure with a Differentiable Simulator
J Ingraham, A Riesselman, C Sander, D Marks
International Conference on Learning Representations, 2019
312019
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
222019
Variational Inference for Sparse and Undirected Models
J Ingraham, D Marks
International Conference on Machine Learning, 2017
20*2017
Generative Models for Graph-Based Protein Design
J Ingraham, VK Garg, R Barzilay, T Jaakkola
Neural Information Processing Systems, 2019
192019
Generating Transition States of Isomerization Reactions with Deep Learning
L Pattanaik, J Ingraham, C Grambow, WH Green
ChemRxiv, 2020
12020
Interpretable Machine Learning for Perturbation Biology
B Yuan, C Shen, A Luna, A Korkut, DS Marks, J Ingraham, C Sander
bioRxiv, 746842, 2019
12019
Interpretable machine learning for perturbation biology
J Shen, B Yuan, A Luna, A Korkut, D Marks, J Ingraham, C Sander
Cancer Research 80 (16 Supplement), 2102-2102, 2020
2020
Probabilistic Models of Structure in Biological Sequences
J Ingraham
2018
Path analysis of vocally-mediated intergroup spacing strategies in mantled howling monkeys
J Ingraham, AL Schreier
AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 144, 173-174, 2011
2011
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Articles 1–15