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.
