Perkins Seminar: Dr Denis Bauer

Event Date and Time:
Thursday 11th April, 2019 @ 12:00pm - 1:00pm

Venue:
McCusker Auditorium, Harry Perkins Institute of Medical Research, Nedlands

Dr Denis Bauer is CSIRO’s Principal Research Scientist in transformational bioinformatics and an internationally recognised expert in machine learning and cloud-based genomics, having presented at AWS Summit, Canberra, 2018 and Open data science conference, India, 2018. Her achievements include developing open-source machine-learning cloud services that accelerate disease research, which is used by 10,000 researchers annually.

Abstract:
Genomic produces more data than Astronomy, twitter, and YouTube combined, having caused research in this discipline to leapfrog to the forefront of cloud technology. Using machine learning and harnessing radically new architecture patterns, a new cloud-native discipline of bioinformatics is emerging.
The talk illustrates this transformation on the example of disease gene discovery. Here, a Spark-based machine learning framework, VariantSpark, was custom designed to deal with ‘wide’ or ultra-high-dimensional data (80 million columns) to find the genetic origin of ALS in 22,000 whole genome sequences. Made available on Amazon Web Services (AWS) and Microsoft Azure through notebook-style access portals, international researchers can explore large volumes of data in real time.
The talk also discusses a new cloud architecture paradigm, serverless, pitted to become an $8 Billion market for its ability to make analysis more economical, akin to how prefabrication scaled up the construction sector over bricklaying. The talk illustrates, the “search engine for the genome” (GT-Scan), a web-service that enables researchers to identify the optimal spot in the 3 billion letter-long genome to make alterations (CRISPR) that one day helps to cure or prevent diseases.
Providing practical tips for the new cloud-native generation of bioinformaticians, the talk compares cloud setups across AWS, Alibaba and Azure and touches on how to evolve cloud architecture more efficiently through a hypothesis-driven approach to DevOps.

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