Harvard plans big data push for computational models of how cells behave

Harvard researchers have licensed GNS Healthcare's REF (Reverse Engineering and Forward Simulation) Big Data analytics platform to build computational models of the mechanisms involved in cell differentiation in hopes of building better treatments.

Beyond learning how cells respond to the different signals they receive, researchers plan to explore how they react to various drugs. They're expected to generate massive amounts of data using whole genome sequencing, RNA sequencing and high-throughput protein measurements collected over time, according to an announcement.

"If we can figure out how to regulate the mechanisms by which cells send signals and coordinate growth throughout the body, we can create better treatments for cancer," said Marc Kirschner, professor and chair of the Department of Systems Biology at Harvard Medical School.

The research is part of the Initiative in Systems Pharmacology, with biologists, chemists, computer scientists, physicists, and mathematicians collaborating on learning how drugs work in the body.

Advancements in gene sequencing and computational capabilities are among the factors behind M.D. Anderson Cancer Center's Moon Shots program, focusing the latest research and technology toward fighting eight common cancers. Ronald A. DePinho, M.D. Anderson's president, has referred to these as a "confluence of enabling technologies" making this a prime time to systematically tackle cancer.

Greater storage capabilities also mean bigger databases. With a $3.75 million grant from the National Cancer Institute, Johns Hopkins researchers plan to store thousands of cell samples in the cloud. By comparing what's going at a genetic level among the large number of samples, they hope to develop more effective treatments.

The American Society of Clinical Oncology, meanwhile, is planning to create a huge database to track, in real time, the treatment effectiveness for thousands of patients. The prototype of the system, known as The CancerLinQ network, is expected to provide "second opinions times multiples."

To learn more:
- find the announcement
- read about the Initiative in Systems Pharmacology

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