MOA Prediction Platform to Help With COVID-19 Research

BioSymetrics Mechanism of Action Prediction Platform framework will be put to work both in prioritizing chemical libraries and in predicting mechanism for identified compounds.

Per the three COVID-19 research initiatives announced by the SCN in the post below, we will be working with William Stanford, Amy Wong, Molly Shoichet, Stephen Juvet, Samira Mubareka, Scott Gray-Own, and Mitchel Sabloff as a component of their research.

We will also have the opportunity to screen one of our own pre-clinical leads.

Please follow us on LinkedIn where were will post updates on this project as they become available.

De-noising CMap L1000 Data

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.

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