RNA Secondary Structure Prediction

Recent trends in RNA informatics: a review of machine learning and deep learning for RNA secondary structure prediction and RNA drug discovery
Computational analysis of RNA sequences constitutes a crucial step in the field of RNA biology. As in other domains of the life …
Kengo Sato, Michiaki Hamada
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RNA Secondary Structure Prediction Based on Energy Models
This chapter introduces the RNA secondary structure prediction based on the nearest neighbor energy model, which is one of the most …
Manato Akiyama, Kengo Sato
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Prediction of RNA secondary structure including pseudoknots for long sequences
RNA structural elements called pseudoknots are involved in various biological phenomena including ribosomal frameshifts. Because it is …
Kengo Sato, Yuki Kato
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RNA secondary structure prediction using deep learning with thermodynamic integration
Accurate predictions of RNA secondary structures can help uncover the roles of functional non-coding RNAs. Although machine …
Kengo Sato, Manato Akiyama, Yasubumi Sakakibara
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A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model
A popular approach for predicting RNA secondary structure is the thermodynamic nearest-neighbor model that finds a thermodynamically …
Manato Akiyama, Kengo Sato, Yasubumi Sakakibara
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Rtips: fast and accurate tools for RNA 2D structure prediction using integer programming
We present a web-based tool set Rtips for fast and accurate prediction of RNA 2D complex structures. Rtips comprises two computational …
Yuki Kato, Kengo Sato, Kiyoshi Asai, Tatsuya Akutsu
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IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming
MOTIVATION: Pseudoknots found in secondary structures of a number of functional RNAs play various roles in biological processes. Recent …
Kengo Sato, Yuki Kato, Michiaki Hamada, Tatsuya Akutsu, Kiyoshi Asai
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