Deep Genomics is building an integrated computational system, the DG Engine, which can learn, predict and interpret how genetic variation, whether natural or therapeutic, alters crucial cellular processes in the context of disease. Unlike other approaches, the DG Engine accounts for the complex, interdependent layers of biological processes that are involved in disease.
The technology developed at Deep Genomics is based on machine learning, a powerful and practical form of artificial intelligence. We develop new machine learning methods that can find patterns in massive datasets and infer computer models of how cells read the genome and generate biomolecules. In this way, our unique technology provides a causal interpretation for genetic variation, not just the correlative information given by industry standard techniques. We can even generate networks of known and unknown variants based on how they affect the same cellular processes, something that was not previously possible. Any variant. Any disease.
Our approach opens the door to a wide range of new techniques for classifying, prioritizing, interpreting and linking genetic variants and genetically derived therapies.
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