Oct 15, 2014 03:38 PM
http://www.sciencedaily.com/releases/201...124923.htm
SNIP Using an innovative algorithm that analyzes gene regulatory and signaling networks, researchers have found that loss of a gene called KLHL9 is the driving force behind the most aggressive form of glioblastoma, the most common form of brain cancer. [...] "Conventional techniques, like genome-wide association studies, must test all possible genetic mutations and variants in a disease cell, compared with a normal cell," said lead author James C. Chen, PhD, a postdoctoral research scientist in Dr. Califano's laboratory, who developed DIGGIT. "These can number in the tens to hundreds of thousands. As a result, based on the number of patients we have profiled, we have sufficient statistical power to identify only the most striking mutations. The DIGGIT algorithm, combined with what we know about regulatory events in the cell, can help us sort through this mass of data and identify critical hidden mutations that otherwise would have gone undetected."
SNIP Using an innovative algorithm that analyzes gene regulatory and signaling networks, researchers have found that loss of a gene called KLHL9 is the driving force behind the most aggressive form of glioblastoma, the most common form of brain cancer. [...] "Conventional techniques, like genome-wide association studies, must test all possible genetic mutations and variants in a disease cell, compared with a normal cell," said lead author James C. Chen, PhD, a postdoctoral research scientist in Dr. Califano's laboratory, who developed DIGGIT. "These can number in the tens to hundreds of thousands. As a result, based on the number of patients we have profiled, we have sufficient statistical power to identify only the most striking mutations. The DIGGIT algorithm, combined with what we know about regulatory events in the cell, can help us sort through this mass of data and identify critical hidden mutations that otherwise would have gone undetected."