As with any assay, L1000 data is noisy. Experimental replicates (the same compound tested on the same cell line under the same conditions) often result in different levels of expression being measured. The process of de-noising the L1000 data makes it easier to see true assay response, and pick a representative concentration for each compound.
When are two compounds the same? The effect of Simplified Molecular Input Line Entry System (SMILES) format on chemical database overlap including best practice for canonicalization and harmonization to understand the impact of these compound effects on a particular dataset and specific application.
CASE STUDY: Machine learning for activity prediction, as part of lead compound generation
The Challenge: The ability to quickly iterate multiple large feature sets with the flexibility to test models at scale is a challenge for any data scientist. Read More