2021/10/06
Keio University
Graduate School of Medical Sciences, Osaka University
A research group, consisting of Senior Assistant Professor Kengo Sato from the Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, and Assistant Professor Yuki Kato from the Graduate School of Medical Sciences, Osaka University, has successfully developed an RNA secondary structure prediction method (IPknot++) capable of predicting complex RNA substructures called pseudoknots. While the prediction of RNA secondary structures including pseudoknots for RNA sequences exceeding several thousand bases has conventionally been extremely difficult from a computational complexity standpoint, this method overcomes this challenge to achieve fast and highly accurate predictions. It is expected to be applied to elucidating gene expression regulatory mechanisms involving pseudoknots in long-chain RNA sequences such as messenger RNA (mRNA) and viral RNA.
The results of this research were published in the online edition of the British scientific journal Briefings in Bioinformatics on October 2, 2021.
Please see below for the full press release.