Taking Cues From Speech Recognition, New Machine Learning Algorithm Finds Patterns in RNA Structures
By Greg Watry
Software inspired by speech recognition technology could help scientists understand the secret language inside cells. A machine learning algorithm called patteRNA, designed by UC Davis researchers, rapidly mines ribonucleic acid, commonly called RNA, for specific structures, providing a new method to establish links between structure, function and disease.
The study, co-authored by integrative genetics and genomics Ph.D. student Mirko Ledda and Assistant Professor Sharon Aviran, UC Davis Genome Center, appears in Genome Biology.
Deciphering the biological role of RNA structures
RNA is essential to all biological processes, from gene expression and regulation to protein synthesis. While DNA stores an organism’s genetic information, RNA puts that genetic information to use.