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pro vyhledávání: '"Watkins, Andrew Martin"'
Autor:
Tagasovska, Nataša, Park, Ji Won, Kirchmeyer, Matthieu, Frey, Nathan C., Watkins, Andrew Martin, Ismail, Aya Abdelsalam, Jamasb, Arian Rokkum, Lee, Edith, Bryson, Tyler, Ra, Stephen, Cho, Kyunghyun
Machine learning (ML) has demonstrated significant promise in accelerating drug design. Active ML-guided optimization of therapeutic molecules typically relies on a surrogate model predicting the target property of interest. The model predictions are
Externí odkaz:
http://arxiv.org/abs/2407.21028
Autor:
Nowara, Ewa M., Pinheiro, Pedro O., Mahajan, Sai Pooja, Mahmood, Omar, Watkins, Andrew Martin, Saremi, Saeed, Maser, Michael
We present NEBULA, the first latent 3D generative model for scalable generation of large molecular libraries around a seed compound of interest. Such libraries are crucial for scientific discovery, but it remains challenging to generate large numbers
Externí odkaz:
http://arxiv.org/abs/2407.03428
Autor:
Pinheiro, Pedro O., Rackers, Joshua, Kleinhenz, Joseph, Maser, Michael, Mahmood, Omar, Watkins, Andrew Martin, Ra, Stephen, Sresht, Vishnu, Saremi, Saeed
We propose a new score-based approach to generate 3D molecules represented as atomic densities on regular grids. First, we train a denoising neural network that learns to map from a smooth distribution of noisy molecules to the distribution of real m
Externí odkaz:
http://arxiv.org/abs/2306.07473
Akademický článek
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