Nazim Bouatta | Machine learning for protein structure prediction, Part 1: Algorithm space

Special Lectures on Machine Learning and Protein Folding 2/9/23 Lecture 1
Speaker: Nazim Bouatta, Harvard Medical School
Title: Machine learning for protein structure prediction, Part 1: Algorithm space
Abstract: AlphaFold2, a neural network-based model which predicts protein structures from amino acid sequences, is revolutionizing the field of structural biology. This lecture series, given by a leader of the OpenFold project which created an open-source version of AlphaFold2, will explain the protein structure problem and the detailed workings of these models, along with many new results and directions for future research.
Lecture 1: Machine learning for protein structure prediction, Part 1: Algorithm space
A brief intro to protein biology. AlphaFold2 impacts on experimental structural biology. Co-evolutionary approaches. Space of ‘algorithms’ for protein structure prediction. Proteins as images (CNNs for protein structure prediction). End-to-end differentiable approaches. Attention and long-range dependencies. AlphaFold2 in a nutshell.

[@Quetz696]

In a nutshell! A tour de force! Great introductie to the field. Can't wait to see the rest.

[@omaviva8657]

Perfect explaination, thank you Mr.Nazim

[@sarthakparikh5988]

fantastic intro!

[@kgmainhosein]

Awesome explanation.

[@Jaeoh.woof765]

40:20 Sequence space -> Structure space
56:00 Protein geometry

[@EdT.-xt6yv]

42:00
45:00 pssm's

[@metipallearuna223]

Mis-sense mutation.