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Computational Method Speeds Mapping of Cell Signaling Networks

For decades, scientists have been studying how external information gets transmitted from outside of cells to the control centers inside them that trigger particular responses. But cell signaling networks are so complex that mapping them has been a slow, arduous process.

Now, a research team from Stanford, MIT and Harvard has developed a new method for charting cellular signaling networks quickly and accurately. Their findings appear in the April 22 issue of Science.

To function properly, cells must be able to detect changes in the environment and respond accordingly--usually by altering their behavior in some way. Cells are equipped with a sophisticated communications network that links surveillance with response, and allows the cells to perform a variety of tasks--such as growing in response to hormones, moving towards a source of nutrients, or responding to foreign invaders in the body. In all of these cases, external signals are converted into cellular messages that get passed sequentially from one molecule to another. Tracing the individual pathways that guide information flow inside cells is a difficult task using standard experimental methods. Multidisciplinary research teams are working on new approaches to make the process faster and easier.

One such group, led by Garry Nolan of Stanford University and Douglas Lauffenburger of MIT has "opened the door for systematic mapping of signaling pathways," according to team member Dana Pe'er. They tested their technique--a combined approach of state-of-the-art experimental and computational methods that "fit like a hand in a glove,"--by mapping a well-studied signaling network in human immune system T-cells. This feat originally took researchers decades to accomplish using traditional approaches.

In the past, scientists have treated signal networks like a puzzle--studying them one pathway at a time and then tying the information together to construct a global picture of what’s going on
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Source:NSF


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