2021/02/12
Keio University
A research group consisting of Senior Assistant Professor Kengo Sato and Professor Yasubumi Sakakibara from the Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, and Manato Akiyama (a third-year student in the Doctoral Programs at the School of Fundamental Science and Technology, Graduate School of Science and Technology, Keio University) has developed a highly accurate and robust RNA secondary structure prediction method (MXFold2) by effectively combining conventional thermodynamic models with deep learning, achieving the world's highest accuracy. This work is expected to have applications in elucidating gene expression mechanisms involving RNA secondary structures and in RNA drug discovery.
The results of this research were published in the online edition of the British scientific journal "Nature Communications" on February 11, 2021.
Please see below for the full press release.