2021/05/05 Dong Si

Dong Si

Dong Si

Assistant Professor at University of Washington Bothell

Artificial Intelligence Advances for De Novo Molecular Structure Modeling in Cryo-EM

Date and time: May 5, 2021

Wednesday, at 8am PT / 11am ET / 3pm GMT / 5pm CET / 11pm China

For the zoom and gather.town links, please join the One World Cryo-EM mailing list.
Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

Although cryo-EM has been drastically improved to generate high-resolution three-dimensional (3D) maps that contain detailed structural information about macromolecules, the computational methods for using the data to automatically build structure models are lagging far behind. The traditional cryo-EM model building approach is template-based homology modeling. Manual de novo modeling is very time-consuming when no template model is found in the database. In recent years, de novo cryo-EM modeling using machine learning (ML) and deep learning (DL) has ranked among the top-performing methods in macromolecular structure modeling. Deep-learning-based de novo cryo-EM modeling is an important application of artificial intelligence, with impressive results and great potential for the next generation of molecular biomedicine. Accordingly, I will talk about the representative ML/DL-based de novo cryo-EM modeling methods that we developed.

2021/05/19 Lauren Ann Metskas

Lauren Ann Metskas

Postdoctoral Fellow at California Institute of Technology
Incoming Assistant Professor at Purdue University

TBD

Date and time: May 19, 2021

Wednesday, at 8am PT / 11am ET / 3pm GMT / 5pm CET / 11pm China

For the zoom and gather.town links, please join the One World Cryo-EM mailing list.
Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

Details TBD