High-accuracy method for identifying disease biomarkers developed by computer scientists

Expert researchers at the University of Waterloo’s Cheriton School of Computer Science (Waterloo, Canada) are developing a deep-learning network for high-accuracy disease biomarker detection by creating a deep neural network that achieves 98% detection of peptide features in a dataset. Alongside existing techniques for disease detection by analyzing the protein structure of biosamples, computer programs are playing a progressive role in this process by examining the large amounts of data produced in such tests to identify specific disease markers. “But existing programs are often inaccurate or can be limited by human error in their underlying functions,” stated Fatema Tuz Zohora,...