Pseudogenes may provide clearer understanding of biomarkers

Han Liang, Ph.D., an assistant professor in the Department of Bioinformatics and Computational Biology at the Cancer Center, and his team completed a study that generated pseudogene expression profiles in 2,808 patient samples representing seven cancer types. That meant analyzing 378 billion RNA sequences to measure the expression levels of close to 10,000 pseudogenes. The results indicated that the science of pseudogene expression analysis may very well play a key role in explaining how cancer occurs by helping medical experts in the discovery of new biomarkers. Read more here.