It’s time for big data to get into the fight against cancer.
We’re working with the National Cancer Institute’s (NCI) Clinical Proteomic Tumor Analysis Consortium to fund researchers using data-intensive computational tools to find new ways to treat cancer.
Up for grabs is a $200,000 grant from the NVIDIA Foundation through its Compute the Cure initiative. At the same time, the Clinical Proteomic Tumor Analysis Consortium will make up to three awards for a total of as much as $1.8 million.
“We’re looking for individuals who can take the data and look at it with a different perspective and ask the questions we haven’t asked, because they’re not obvious to us,” says Henry Rodriguez, director of the NCI’s Office of Cancer Clinical Proteomics Research.
The big idea is something researchers like Rodriguez have nicknamed “-omics.” It’s a slangy term for the growing ability to collect big piles of data on the three major classes of molecules essential to all forms of life.
They include: DNA, molecules that contain the genetic code in our genes; RNA, molecules that carry the genetic information out of the nucleus and into the rest of the cell; and proteins, molecules created from the information carried by RNA that ultimately become the workhorses of a cell.
Sequencing the DNA has already resulted in breakthroughs. The challenge is that the approach doesn’t always work, says Christopher Kinsinger, the technology program manager for the NCI’s Clinical Proteomic Tumor Analysis Consortium.
Taking a step back and looking at how all the major classes of molecules interact – DNA, RNA and proteins – promises to explain why. And it could yield new treatments for stubborn cancers.
“If you begin to integrate those different types of -omics, you get additional information not inferred by simply mining genomic data,” Kinsinger says.
To help, we’re each seeking proposals from researchers looking for new ways to use computing power to understand this data. (And, to be clear, while the NCI supports similar goals as the NVIDIA Foundation’s Compute the Cure initiative, it’s a wholly independent organization.)
Project areas we’ll consider for funding: the development of new computational tools, the integration of new computational analysis techniques and the development of innovative simulation and visualization methods.
We have two goals. First, help researchers who are developing ways to advance the diagnosis, treatment or prevention of cancer. Second, make computational biology accessible to research scientists who don’t have programming experience.
In other words, we want to put computing in the middle of the fight against cancer.