Building Chemogenomics Models from a Large-Scale Public Dataset and Applying them to Industrial Datasets

author: Noé Sturm, AstraZeneca
published: June 28, 2019,   recorded: May 2019,   views: 63


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


ExCAPE was a European funded project aiming at harvesting the power of supercomputers to speed up drug discovery ( Thanks to the project team, we were given the amazing opportunity to build large-scale machine learning models for compound activity predictions from public databases and to apply them to industrial datasets. In this talk, I will present the process of collecting chemogenomics data from public resources to build a benchmark dataset. Subsequently, I will explain the process of building and evaluating the performance of models built with multi-task deep learning and matrix factorization algorithms. Ultimately, I will show how these models were applied to industrial datasets.

See Also:

Download slides icon Download slides: icgeb_sturm_chemogenomics_models_01.pdf (5.1 MB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 fredluis, October 9, 2019 at 7:17 a.m.:

The author has written an excellent article. You made your point and not much to discuss. It's like this universal truth that you can not argue with the truth is not universal, everything has its exception. Thanks for this information.

Comment2 Danny, January 1, 2020 at 6:32 p.m.:

Wow you have a great article. Thanks for sharing this! <a href=""></a>

Write your own review or comment:

make sure you have javascript enabled or clear this field: