Compared with a long-used linear model, a correlation-based statistical method is a more reliable way to map complex gene interactions and pinpoint genes that may be potential cancer treatment targets, according to new Brown University research.
The research is important because it describes a promising new tool for tracing human gene connections, a task critical for understanding and treating cancer and other diseases. Results appeared this week in the online edition of the Proceedings of the National Academy of Sciences. “Genes influence one another in many intricate ways,” said Leon Cooper, professor of physics and neuroscience and director of the Institute for Brain and Neural Systems at Brown. “What we need is a map, or network, of these links. What we’ve identified in this project is a more effective method for making this map.”
The research team – which included scientists from the fields of biology, physics, statistics and computer science at Brown, Università di Bologna in Italy and Tel Aviv University in Israel – set out to answer a question. When a deadly “oncoprotein” is switched on, what chain reaction of gene activity does it set off?
Wendy Lawton | EurekAlert!
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