Cutting-edge computer software helps pinpoint aggressiveness of breast cancer tumors — ScienceDaily
Their findings are published today in the journal, Nature Scientific Reports. …
Their findings are published today in the journal, Nature Scientific Reports. …
Their findings are published today in the journal, Nature Scientific Reports. “We are using a unique software program in our lab that looks at a type of mutation called a splicing mutation that is typically overlooked using current methods,” said lead author on the study, Stephanie Dorman, a PhD student in the department of biochemistry at Western University’s Schulich School of Medicine & Dentistry. She said that where previous genetic studies of 445 tumours detected 429 of these splicing mutations, the Western-developed analysis software was able to find more than 5000. Using this software and human tumour tissue sample genetic data from The Cancer Genome Atlas, the research team pinpointed that mutations in the Neural Cell Adhesion Molecule (NCAM) and other related genes in NCAM biology were present at a much higher rate in tumours which had metastasized to the lymph nodes than those that did not…
The study, the most comprehensive analysis ever conducted of RNA molecules in human saliva, reveals that saliva contains many of the same disease-revealing molecules that are contained in blood. It was published online today by the peer-reviewed journal Clinical Chemistry and will be published in the journal’s January 2015 special print issue, “Molecular Diagnostics: A Revolution in Progress.” “If we can define the boundaries of molecular targets in saliva, then we can ask what the constituents in saliva are that can mark someone who has pre-diabetes or the early stages of oral cancer or pancreatic cancer — and we can utilize this knowledge for personalized medicine,” said Dr…
The research, recently published online ahead of print by the Proceedings of the National Academy of Sciences, shows that a pair of proteins joined together by a genetic mutation — known as CRTC1/MAML2 (C1/M2) — work with MYC, a protein commonly associated with other cancers, to promote the oral cancer’s growth and spread. “This research provides new insights into the molecular mechanisms of these malignances and points to a new direction for potential therapies,” says TSRI biologist Michael Conkright, PhD, who led the study…
The results of their study are published in the journal Cancer Cell. The research team led by Sloan-Kettering researchers studied a tumor suppressor called Merlin. …
source : http://www.sciencedaily.com/releases/2014/07/140710130510.htm
source : http://www.sciencedaily.com/releases/2014/04/140424125305.htm
source : http://www.sciencedaily.com/releases/2014/04/140422152819.htm
Since each cell in the body contains 23,000 genes, identifying the specific genes involved in cancer growth is an exceedingly complex task. Researchers used a form of artificial intelligence called machine learning to identify three genes that allowed them to determine whether a tumour was fed by estrogen. "People can’t possibly sort through all this information and find the important patterns," said senior author Russ Greiner, a professor in the Department of Computing Science and investigator with the Alberta Innovates Centre for Machine Learning. …
Duo Zhou, a biostatistician at pharmaceutical company Pfizer in New York and colleagues Dinesh Mital and Shankar Srinivasan of the University of Medicine and Dentistry of New Jersey, point out that data pattern recognition is widely used in machine-learning applications in science. Computer algorithms trained on historical data can be used to analyze current information and detect patterns and then predict possible future patterns. However, this powerful knowledge discovery technology is little used in medicine…