Machine Learning, AI and Biology

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The integration of Machine Learning and AI with the brightest minds in the biological sciences unlocks immense potential for groundbreaking discoveries. Scientists in the School of Biological Sciences are harnessing the power of machine learning and large-scale data to drive innovation across three core areas: breakthrough biology; transforming health; and environmental resilience.

Breakthrough Biology

Cambridge scientists are applying machine learning technologies across biological systems, from tracking DNA replication and repair processes within cells, to modelling cellular growth and regeneration, and developing neural models of learning and memory. These interdisciplinary approaches are having transformative impact in unravelling the complexities of biological system and will rapidly drive knowledge expansion and real-world impacts.

Transforming Health

AI and Machine Learning had the potential to significantly transform our approach to human health, and researchers in the School are harnessing this opportunity across numerous areas, including: the development of diagnostic and predictive models of complex diseases linked to the gut microbiome; applying AI technology to create tools for diagnosis and treatment of brain mental health disorders; and accelerating drug discovery with enhanced screening of drug receptors and their binding partners. Working collaboratively with industry partners and clinicians, these new discoveries have the potential to transform the future of human health.

Environmental Resilience

Researchers working to understand the complexities of organisms, evolutions and environmental resilience are leveraging the power of AI and Machine Learning to accelerate progress in this priority area. Our scientists are harnessing the latest technology across a range of projects, including: automating species identification and driving understanding of the earliest life on earth; monitoring and trailing endangered species as part of important conservation work; and identifying and monitoring pathogens in plants, animals and humans to inform disease modelling and intervention strategies. Combining world-leading expertise on organisms, evolutions and the environment with the power of AI and machine learning will drive novel solutions to some of the most pressing challenges the planet currently faces.