Unlocking cancer's secrets using the 'social networks' of cells
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IMAGE: Megha Padi, Ph.D., director of the UA Cancer Center Bioinformatics Shared Resource and an assistant professor of molecular and cellular biology, developed a computer algorithm called ALPACA that reveals which… view more 

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TUCSON, Ariz. – Recent headlines have cast suspicion on social network analysis, which can mine data from the internet to target advertisements or potentially influence elections.

But what if we could use those same tools not for the economic or political gain of a few, but for the health of all humankind? Scientists now can harness the tools of social network analysis to understand connections among genes, an advance that someday could lead to medical advancements.

Megha Padi, PhD, director of the UA Cancer Center Bioinformatics Shared Resource and an assistant professor of molecular and cellular biology, developed a computer algorithm called ALPACA that reveals which gene networks are activated in a diseased cell — an approach that could lead to better treatments for various diseases. The results were published online April 19 in the open-access Nature Partner journal Systems Biology and Applications.

Cancer researchers usually focus on specific genes when comparing healthy cells to tumor cells, an approach that does not completely explain what occurs behind

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