Our team behind the scenes at SXSW | Target Identification, Literature Knowledge Inference


Watch our team investigate the target identification process for Glioblastoma (GBM) using machine learning methods. Our aim was to identify genes or proteins involved in the development of glioblastoma stem cells - a type of cell at the origin of GBM that is resistant to current treatments.

After creating a knowledge base around the disease (see episode 2) our team created a specific workflow around literature based data. By applying AI models, each interrogating a different component of the data sets, we can generate a list of possible hypotheses for genes involved in GBM.

It is important to train machine learning to do what we consider tedious, yet critical tasks. It frees up scientists to focus their energy on exploring hypotheses.

Watch our team discuss the unique way we approach target identification at BenevolentAI.


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Patient Stratification in Target ID, OMICS data