"Exponential data problems is very challenging and it's why it's hard to apply machine learning to genomics"

"Sequencing 1M genomes or 1B genomes won't address these problems"

Last week at the Deep Learning Summit in San Francisco we had lots of great speakers including Brendan Frey, Co-Founder & CEO at Deep Genomics; Andrew Tulloch, Research Engineer at Facebook and Andrej Karpathy, Research Scientist at OpenAI, amongst many others.

Incase you missed the presentation from Brendan Frey from Deep Genomics, we are sharing with you the full recording of the video below!

Deep Genomics bring together machine learning and experimental biology. Their systems "predict the molecular effect of genetic variation, opening a new and exciting path to discovery for disease diagnostics and therapies." Brenden talks about the recently developed gene editing systems that has made it possible to edit our genomes. His talk focused around why machine learning and AI will play a central role in this transformation of medicine and of humanity.

Spinal Muscular Atrophy is the leading cause of infant mortality with 1/10,000 births. In 2016, the therapy by Deep Genomics was declared successful however it was believed the time for development would take 13 years. Deep Genomics' goal is to use machine learning and AI to reduce that time to 3 years. "The opportunity is to improve life!"

Check out the full session below:

Q&A During the Summit

1. There are lots of different kinds of datasets and cell lines to look at, why have you concentrated on one area?

We need to be focussed to crack one thing at a time. We will crack other organism types in the future.

2. What problems have you faced?

There are lots of different techniques. Setting out the problems is taking a lot of time.

3. What are the ethical implications of what you do?

Our goal is to help people. In the future, it's hard to say what that will look like and people fear uncertainty. However, keeping everything the same and static is not an option. Humans are about embracing change and I feel there will be a better understanding between biology and the relationship with genomes.

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