Roshan Rao

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Tom SercuFacebook AI ResearchVerified email at fb.com
Alexander RivesNew York UniversityVerified email at cs.nyu.edu
John CannyUniversity of California, BerkeleyVerified email at cs.berkeley.edu
Nicholas BhattacharyaPhD, UC BerkeleyVerified email at berkeley.edu
Neil ThomasResearch Scientist, [Google] XVerified email at berkeley.edu
Joshua MeierResearch Engineer, Facebook AI ResearchVerified email at fb.com
Pieter AbbeelUC Berkeley | CovariantVerified email at cs.berkeley.edu
Sergey OvchinnikovMITVerified email at mit.edu
David ChanUniversity of California, BerkeleyVerified email at berkeley.edu
(Peter) Xi Chencovariant.ai | UC BerkeleyVerified email at berkeley.edu
Yan DuanCovariant.AIVerified email at covariant.ai
Forrest HuangResearch Scientist, AppleVerified email at apple.com
Justas DauparasUniversity of WashingtonVerified email at uw.edu
Peter KooAssistant Professor, Cold Spring Harbor LaboratoryVerified email at cshl.edu
David BakerUniversity of WashingtonVerified email at uw.edu
Daniel SeitaUniversity of Southern CaliforniaVerified email at usc.edu
Sudha RaoMicrosoft ResearchVerified email at microsoft.com
Elnaz NouriMicrosoft ResearchVerified email at usc.edu
Bill DolanPartner Research Manager, Microsoft ResearchVerified email at microsoft.com
Debadeepta DeyPrincipal Researcher, Microsoft Research | Azure AIVerified email at microsoft.com

Roshan Rao

Research Scientist

Verified email at evolutionaryscale.ai - Homepage

Protein Design Unsupervised Learning


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Evolutionary-scale prediction of atomic-level protein structure with a language model Z Lin, H Akin, R Rao, B Hie, Z Zhu, W Lu, N Smetanin, R Verkuil, O Kabeli, ... Science 379 (6637), 1123-1130, 2023	1316*	2023
Evaluating protein transfer learning with TAPE R Rao, N Bhattacharya, N Thomas, Y Duan, P Chen, J Canny, P Abbeel, ... Advances in neural information processing systems 32, 2019	753	2019
MSA transformer RM Rao, J Liu, R Verkuil, J Meier, J Canny, P Abbeel, T Sercu, A Rives International Conference on Machine Learning, 8844-8856, 2021	459	2021
Language models enable zero-shot prediction of the effects of mutations on protein function J Meier, R Rao, R Verkuil, J Liu, T Sercu, A Rives Advances in neural information processing systems 34, 29287-29303, 2021	352	2021
Transformer protein language models are unsupervised structure learners R Rao, J Meier, T Sercu, S Ovchinnikov, A Rives Biorxiv, 2020.12. 15.422761, 2020	241	2020
GPU accelerated t-distributed stochastic neighbor embedding DM Chan, R Rao, F Huang, JF Canny Journal of Parallel and Distributed Computing 131, 1-13, 2019	174*	2019
Single layers of attention suffice to predict protein contacts N Bhattacharya, N Thomas, R Rao, J Dauparas, PK Koo, D Baker, ... Biorxiv, 2020.12. 21.423882, 2020	30	2020
End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman S Petti, N Bhattacharya, R Rao, J Dauparas, N Thomas, J Zhou, AM Rush, ... Bioinformatics 39 (1), btac724, 2023	24	2023
A high-level programming language for generative protein design B Hie, S Candido, Z Lin, O Kabeli, R Rao, N Smetanin, T Sercu, A Rives bioRxiv, 2022.12. 21.521526, 2022	21	2022
ZPD teaching strategies for deep reinforcement learning from demonstrations D Seita, D Chan, R Rao, C Tang, M Zhao, J Canny arXiv preprint arXiv:1910.12154, 2019	11	2019
Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features A Harmalkar, R Rao, Y Richard Xie, J Honer, W Deisting, J Anlahr, ... Mabs 15 (1), 2163584, 2023	8	2023
Interpreting potts and transformer protein models through the lens of simplified attention N Bhattacharya, N Thomas, R Rao, J Dauparas, PK Koo, D Baker, ... PACIFIC SYMPOSIUM ON BIOCOMPUTING 2022, 34-45, 2021	7	2021
Quality and relevance metrics for selection of multimodal pretraining data R Rao, S Rao, E Nouri, D Dey, A Celikyilmaz, B Dolan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020	1	2020
Training, Evaluating, and Understanding Evolutionary Models for Protein Sequences RM Rao University of California, Berkeley, 2021		2021
Seq2MSA: A Language Model for Protein Sequence Diversification P Sturmfels, R Rao, R Verkuil, Z Lin, O Kabeli, T Sercu, A Lerer, A Rives

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