The Multi-Facets of a Data Science Project to Answer: How Are Organs Formed?

• Activity Number: 461
• Type: Invited
• Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
• Sponsor: ASA
• Author(s): Bin Yu*
• Companies: UC Berkeley

Abstract

In this talk, I present results from a data science project co-led by biologist Frise from LBNL to answer the question in the talk title. We create a novel image representation decomposing spatial data into building blocks (or principal patterns). These principal patterns provide an innovative and biologically meaningful approach for the interpretation and analysis of large complex spatial data. They are the basis for constructing local gene networks, and we have been able to reproduced almost all the links in the Nobel-prize winning (local) gap-gene network. Knock-out experiments are being carried out to validate our predictions on gene-gene interactions and relevant theoretical results are obtained.Our team consists of Wu, Joseph, Kumbier from my group, Frise and other biologists (Hommands) in Celniker's Lab at LBNL that generate the Drosophila spatial expression embryonic image data, and Xu from Tsinghua Univ to devise a scalable open software package.