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Stephen Ra
Stephen Ra
Director, Prescient Design, Genentech
Verified email at gene.com - Homepage
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Cited by
Year
Opportunities and obstacles for deep learning in biology and medicine
T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ...
Journal of the royal society interface 15 (141), 20170387, 2018
19642018
FAAH genetic variation enhances fronto-amygdala function in mouse and human
I Dincheva, AT Drysdale, CA Hartley, DC Johnson, D Jing, EC King, S Ra, ...
Nature communications 6 (1), 6395, 2015
2812015
Forebrain elimination of cacna1c mediates anxiety-like behavior in mice
AS Lee, S Ra, AM Rajadhyaksha, JK Britt, D Jesus-Cortes, KL Gonzales, ...
Molecular psychiatry 17 (11), 1054-1055, 2012
1112012
OpenFold: Retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization
G Ahdritz, N Bouatta, C Floristean, S Kadyan, Q Xia, W Gerecke, ...
Nature Methods, 1-11, 2024
1052024
Cav1. 2 L-type Ca2+ channels mediate cocaine-induced GluA1 trafficking in the nucleus accumbens, a long-term adaptation dependent on ventral tegmental area Cav1. 3 channels
K Schierberl, J Hao, TF Tropea, S Ra, TP Giordano, Q Xu, SM Garraway, ...
Journal of Neuroscience 31 (38), 13562-13575, 2011
862011
Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data
AM Smith, JR Walsh, J Long, CB Davis, P Henstock, MR Hodge, ...
BMC bioinformatics 21, 1-18, 2020
622020
Behavioral characterization of cereblon forebrain-specific conditional null mice: a model for human non-syndromic intellectual disability
AM Rajadhyaksha, S Ra, S Kishinevsky, AS Lee, P Romanienko, ...
Behavioural brain research 226 (2), 428-434, 2012
562012
Function-guided protein design by deep manifold sampling
V Gligorijević, D Berenberg, S Ra, A Watkins, S Kelow, K Cho, R Bonneau
bioRxiv, 2021.12. 22.473759, 2021
352021
Equifold: Protein structure prediction with a novel coarse-grained structure representation
JH Lee, P Yadollahpour, A Watkins, NC Frey, A Leaver-Fay, S Ra, K Cho, ...
Biorxiv, 2022.10. 07.511322, 2022
252022
FAAH genetic variation enhances fronto-amygdala function in mouse and human. Nat Commun 6: 6395
I Dincheva, AT Drysdale, CA Hartley, DC Johnson, D Jing, EC King, S Ra, ...
222015
Learning causal representations of single cells via sparse mechanism shift modeling
R Lopez, N Tagasovska, S Ra, K Cho, J Pritchard, A Regev
Conference on Causal Learning and Reasoning, 662-691, 2023
192023
PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design
JW Park, S Stanton, S Saremi, A Watkins, H Dwyer, V Gligorijevic, ...
arXiv preprint arXiv:2210.04096, 2022
112022
Deep learning of representations for transcriptomics-based phenotype prediction
AM Smith, JR Walsh, J Long, CB Davis, P Henstock, MR Hodge, ...
BioRxiv, 574723, 2019
82019
Protein discovery with discrete walk-jump sampling
NC Frey, D Berenberg, K Zadorozhny, J Kleinhenz, J Lafrance-Vanasse, ...
arXiv preprint arXiv:2306.12360, 2023
72023
A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences
N Tagasovska, NC Frey, A Loukas, I Hötzel, J Lafrance-Vanasse, RL Kelly, ...
arXiv preprint arXiv:2210.10838, 2022
62022
OpenProteinSet: Training data for structural biology at scale
G Ahdritz, N Bouatta, S Kadyan, L Jarosch, D Berenberg, I Fisk, A Watkins, ...
Advances in Neural Information Processing Systems 36, 2024
52024
Black box recursive translations for molecular optimization
F Damani, V Sresht, S Ra
arXiv preprint arXiv:1912.10156, 2019
52019
3D molecule generation by denoising voxel grids
PO O Pinheiro, J Rackers, J Kleinhenz, M Maser, O Mahmood, A Watkins, ...
Advances in Neural Information Processing Systems 36, 2024
42024
Multi-segment preserving sampling for deep manifold sampler
D Berenberg, JH Lee, S Kelow, JW Park, A Watkins, V Gligorijević, ...
arXiv preprint arXiv:2205.04259, 2022
32022
Learning protein family manifolds with smoothed energy-based models
NC Frey, D Berenberg, J Kleinhenz, I Hotzel, J Lafrance-Vanasse, ...
ICLR 2023 Workshop on Physics for Machine Learning, 2023
22023
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