openkinome / kinoml

Structure-informed machine learning for kinase modeling
https://openkinome.org/kinoml/
MIT License
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Modeling updates #34

Closed schallerdavid closed 3 years ago

schallerdavid commented 3 years ago

Description

This PR adds important updates, new functionalities and tests to the KinoML modeling pipeline.

Todos

Notable points that this PR has either accomplished or will accomplish.

Status

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schallerdavid commented 3 years ago

Hi @t-kimber and @jaimergp ,

I merged master into this branch. This branch adds several improvements to the structural modeling pipeline and additionally adds tests. Pytest only reports a single failure, but this is intended since it is simply not implemented yet. My complex featurizers seem to work. Is there anything else I can test or you want to test before I merge this into master?

Cheers, David

jaimergp commented 3 years ago

"Pipeline" tests are done in https://github.com/openkinome/experiments-binding-affinity. Talia should be able to tell you how to add your featurizers to some examples there and run it locally!

codecov-commenter commented 3 years ago

Codecov Report

Merging #34 (2889cca) into master (4b24e11) will increase coverage by 11.73%. The diff coverage is 46.63%.

schallerdavid commented 3 years ago

Except for test_access_by_index_roundtrip all tests are passing. But this is not implemented yet. The featurization tests in experiments-binding-affinity are passing but not the model training. However, this was already the case with the current master (see #13). Merging now.