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Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction


Jan 28, 2023
Zuobai Zhang, Minghao Xu, Aurélie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang

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Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models


Oct 13, 2022
Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das

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AlphaFold Distillation for Improved Inverse Protein Folding


Oct 05, 2022
Igor Melnyk, Aurelie Lozano, Payel Das, Vijil Chenthamarakshan

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* Preprint 

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Cloud-Based Real-Time Molecular Screening Platform with MolFormer


Aug 13, 2022
Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young

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* Paper accepted at ECML PKDD 2022 demo track 

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GT4SD: Generative Toolkit for Scientific Discovery


Jul 08, 2022
Matteo Manica, Joris Cadow, Dimitrios Christofidellis, Ashish Dave, Jannis Born, Dean Clarke, Yves Gaetan Nana Teukam, Samuel C. Hoffman, Matthew Buchan, Vijil Chenthamarakshan, Timothy Donovan, Hsiang Han Hsu, Federico Zipoli, Oliver Schilter, Giorgio Giannone, Akihiro Kishimoto, Lisa Hamada, Inkit Padhi, Karl Wehden, Lauren McHugh, Alexy Khrabrov, Payel Das, Seiji Takeda, John R. Smith

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* 7 pages, 3 figures 

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Learning Geometrically Disentangled Representations of Protein Folding Simulations


May 20, 2022
N. Joseph Tatro, Payel Das, Pin-Yu Chen, Vijil Chenthamarakshan, Rongjie Lai

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* 13 pages, appeared at SimDL ICLR Workshop 2021 

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Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework


Apr 19, 2022
Vijil Chenthamarakshan, Samuel C. Hoffman, C. David Owen, Petra Lukacik, Claire Strain-Damerell, Daren Fearon, Tika R. Malla, Anthony Tumber, Christopher J. Schofield, Helen M. E. Duyvesteyn, Wanwisa Dejnirattisai, Loic Carrique, Thomas S. Walter, Gavin R. Screaton, Tetiana Matviiuk, Aleksandra Mojsilovic, Jason Crain, Martin A. Walsh, David I. Stuart, Payel Das

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Protein Representation Learning by Geometric Structure Pretraining


Mar 14, 2022
Zuobai Zhang, Minghao Xu, Arian Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang

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Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model


Dec 02, 2021
Samuel C. Hoffman, Vijil Chenthamarakshan, Dmitry Yu. Zubarev, Daniel P. Sanders, Payel Das

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Benchmarking deep generative models for diverse antibody sequence design


Nov 12, 2021
Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurelie Lozano

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* Learning Meaningful Representations of Life Workshop paper at NeurIPS 2021 

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