Chapter
Protein Structure Prediction with Machine Learning
1:10:13 - 1:20:08 (09:54)
The speaker discusses how when a protein is being translated, there is already some structural fragmentation happening, and how state-of-the-art machine learning systems can be used for structure prediction. This includes a combination of biophysics and bioinformatics in order to obtain protein structures of proteins without any known structure.
Clips
This podcast talks about the different ways scientists predict protein functions, predict the effects of mutations on protein functions, and predict protein-protein interactions, as well as the relevance of understanding protein folding mechanisms.
1:10:13 - 1:14:34 (04:21)
Summary
This podcast talks about the different ways scientists predict protein functions, predict the effects of mutations on protein functions, and predict protein-protein interactions, as well as the relevance of understanding protein folding mechanisms.
ChapterProtein Structure Prediction with Machine Learning
Episode#153 – Dmitry Korkin: Evolution of Proteins, Viruses, Life, and AI
PodcastLex Fridman Podcast
Researchers have developed a state-of-the-art machine learning system that combines biophysics, bioinformatics, and data mining to obtain protein structures through comparative modeling called homology, even where none exist.
1:14:34 - 1:20:08 (05:33)
Summary
Researchers have developed a state-of-the-art machine learning system that combines biophysics, bioinformatics, and data mining to obtain protein structures through comparative modeling called homology, even where none exist.