In this webinar, Dr. Seth Harris, Director of Computational Structural Biology & Senior Principal Scientist at Genentech, talks about GYST, the XR-integrated system developed by Genentech to efficiently manage large structural datasets.
At Genentech, the in-house GYST platform is used to explore annotated structural datasets and rapidly get insights from large amounts of structural information.
GYST integrates Nanome in its systems and allows researchers to access information, and manipulate and visualize data in the immersive virtual reality environment. During the webinar, Dr. Harris will go over the collaboration between scientists at Genentech and the Nanome team that led to the creation of customized GYST plugins.
Highlights:
- Large-scale data extracts and annotations of structural features can accelerate drug discovery and research
- Our in-house platform GYST creates such datasets and enables their exploration by a broad range of researchers, while also provisioning information for machine-learning models
- Custom plugins enable seamless integration of Nanome as a visualization and analytical component in this system
In this webinar, Dr. Seth Harris, Director of Computational Structural Biology & Senior Principal Scientist at Genentech, talks about GYST, the XR-integrated system developed by Genentech to efficiently manage large structural datasets.
At Genentech, the in-house GYST platform is used to explore annotated structural datasets and rapidly get insights from large amounts of structural information.
GYST integrates Nanome in its systems and allows researchers to access information, and manipulate and visualize data in the immersive virtual reality environment. During the webinar, Dr. Harris will go over the collaboration between scientists at Genentech and the Nanome team that led to the creation of customized GYST plugins.
Highlights:
- Large-scale data extracts and annotations of structural features can accelerate drug discovery and research
- Our in-house platform GYST creates such datasets and enables their exploration by a broad range of researchers, while also provisioning information for machine-learning models
- Custom plugins enable seamless integration of Nanome as a visualization and analytical component in this system