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2310.10605
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ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a protein language diffusion model
16 October 2023
Bo Ni
David L. Kaplan
Markus J. Buehler
DiffM
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Papers citing
"ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a protein language diffusion model"
5 / 5 papers shown
Title
Sifting through the Noise: A Survey of Diffusion Probabilistic Models and Their Applications to Biomolecules
Trevor Norton
Debswapna Bhattacharya
MedIm
DiffM
50
2
0
31 May 2024
ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learning
Alireza Ghafarollahi
Markus J. Buehler
LLMAG
AI4CE
13
23
0
27 Jan 2024
MechAgents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledge
Bo Ni
Markus J. Buehler
AI4CE
LLMAG
15
39
0
14 Nov 2023
Diffusion-LM Improves Controllable Text Generation
Xiang Lisa Li
John Thickstun
Ishaan Gulrajani
Percy Liang
Tatsunori B. Hashimoto
AI4CE
173
777
0
27 May 2022
Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models
N. Anand
Tudor Achim
DiffM
187
173
0
26 May 2022
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