1 code implementation • 15 Nov 2023 • Gian Marco Visani, William Galvin, Michael Neal Pun, Armita Nourmohammad
Accurately modeling protein 3D structure is essential for the design of functional proteins.
1 code implementation • 30 Sep 2022 • Gian Marco Visani, Michael N. Pun, Arman Angaji, Armita Nourmohammad
Group-equivariant neural networks have emerged as a data-efficient approach to solve classification and regression tasks, while respecting the relevant symmetries of the data.
1 code implementation • 28 Apr 2021 • Gian Marco Visani, Alexandra Hope Lee, Cuong Nguyen, David M. Kent, John B. Wong, Joshua T. Cohen, Michael C. Hughes
We develop an Approximate Bayesian Computation approach that draws samples from the posterior distribution over the model's transition and duration parameters given aggregate counts from a specific location, thus adapting the model to a region or individual hospital site of interest.
1 code implementation • 18 Feb 2020 • Gian Marco Visani, Michael C. Hughes, Soha Hassoun
Some interactions are attributed to natural selection and involve the enzyme's natural substrates.