Health / Pharma

Visualizing the Big Data of Breast Cancer

A colorful wheel developed by Rice University bioengineers to visualize protein interactions has won an international competition for novel strategies to study the roots of breast cancer.

The winning BioWheel by the Rice lab of bioengineer Amina Qutub was chosen this month, topping 14 academic and industry participants in the HPN-DREAM Breast Cancer Network Inference Challenge. Qutub has been invited to present the lab’s creation at the RECOMB/ISCB conference on Regulatory and Systems Genomics in Toronto next month.

The Rice team led by graduate student Wendy Hu won one of three sub-challenges to create an intuitive, interactive tool to visualize “big data.” In this case, that involved hundreds of thousands of data points about the effects of stimulators and inhibitors on protein networks drawn from a set of four breast cancer cell lines. Team members include postdoctoral researchers Byron Long and Dave Noren and undergraduate student Alex Bisberg.

All of the competitors were presented with the same data set. The idea, according to organizers, was to develop maps that increase the understanding of protein signaling in cancer cells and accelerate the development of treatments. Organizers of the crowdsource-style competition hoped that having dozens of participants work on the same data for four months would produce results that might otherwise take a single group many years.

“The task is to help people interpret intricate patterns that are very hard to see in high-dimensional data,” said Qutub, an assistant professor of bioengineering based at Rice’s BioScience Research Collaborative. Massive amounts of data can be produced when researchers study how healthy or cancerous cell lines taken from patients respond to stimulants, like drugs that up- or down-regulate protein interactions.

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