Advances in AI can help advance genomics by helping to predict the effects of changes to DNA structures. This can be used to help medical diagnostics, create better vaccinations and support research into crop breeding.
Stockholm, 26 November, 2018
A paper published today in the world’s leading scientific journal in genomics, Nature Genetics, reviews the success of artificial intelligence (AI) techniques, especially deep learning, in analyzing the genome and predicting the effects of changes in DNA. The paper concludes that artificial intelligence has already demonstrated impressive potential in genomics, and that the technology can potentially be used for synthetic biology by learning how to automatically generate new DNA sequences with specific desirable properties.
The paper assesses many recent breakthroughs using a particular type of AI known as ‘deep learning.’ The co-authors of the paper are James Zou of the Stanford University School of Medicine and the Chan-Zuckerberg Biohub; Mikael Huss of the operational AI platform company, Peltarion, and the Karolinska Institutet in Sweden; Abubakar Abid of the Stanford School of Medicine; and Ali Torkamani, Pejman Mohammadi and Amalio Telenti, of the Scripps Research Institute.
The authors have also launched an interactive online tutorial to help introduce deep-learning AI to other genomic researchers and scientists. Aimed at both AI experts and genomics researchers, the tutorial provides an easy-to-use playbook on how to harness the power of AI specifically for the purpose of genomics research.
Predicting the effects of changes in DNA sequences is crucial in many fields of genomics and is an integral part of new medical diagnostics, vaccine development, and innovations in plant breeding. AI can help by spotting patterns in large quantities of data, which would have been difficult, if not impossible, for humans to see or understand.
In genomics, researchers need to understand not just the effect of a single change of DNA, but multiple changes; this work is currently done in lab experiments, which is costly and time-consuming. Using AI, researchers can save time and money by building an AI-model which can allow them to do more with less, and faster.
Peltarion provides an operational AI platform for producing real-world AI applications at scale and speed. Founded in 2004, over 300 companies and organizations have used Peltarion’s AI technology including NASA, Tesla, iZettle, General Electric, Dell, BMW, Deutsche Bank, Lloyds Banking Group, and the Universities of Harvard, MIT and Oxford. Our mission is to make AI technology useable and affordable for all.
About Scripps Research Translational Institute
The Scripps Research Translational Institute, formerly named Scripps Translational Science Institute (STSI), was founded in 2007 with one essential aim—to individualize healthcare by leveraging the remarkable progress being made in human genomics and combining it with the power of wireless digital technologies. By recognizing that every patient is unique, individualized healthcare tailors medical care to the patient, taking into account not only a person’s genes, but also their environment, behavior and lifestyle. Bringing together basic scientists and clinical investigators, the Translational Institute fosters highly collaborative multidisciplinary research with the greatest potential to transform the practice of healthcare and improve human health.