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Web Services for RNA-RNA Interaction Prediction.
Fukunaga, Tsukasa; Iwakiri, Junichi; Hamada, Michiaki.
Affiliation
  • Fukunaga T; Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. fukunaga@aoni.waseda.jp.
  • Iwakiri J; Waseda Institute for Advanced Study, Waseda University, Tokyo, Japan. fukunaga@aoni.waseda.jp.
  • Hamada M; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Methods Mol Biol ; 2586: 175-195, 2023.
Article in En | MEDLINE | ID: mdl-36705905
ABSTRACT
Non-coding RNAs have various biological functions such as translational regulation, and RNA-RNA interactions play essential roles in the mechanisms of action of these RNAs. Therefore, RNA-RNA interaction prediction is an important problem in bioinformatics, and many tools have been developed for the computational prediction of RNA-RNA interactions. In addition to the development of novel algorithms with high accuracy, the development and maintenance of web services is essential for enhancing usability by experimental biologists. In this review, we survey web services for RNA-RNA interaction predictions and introduce how to use primary web services. We present various prediction tools, including general interaction prediction tools, prediction tools for specific RNA classes, and RNA-RNA interaction-based RNA design tools. Additionally, we discuss the future perspectives of the development of RNA-RNA interaction prediction tools and the sustainability of web services.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: RNA / MicroRNAs Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2023 Document type: Article Affiliation country: Japón

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: RNA / MicroRNAs Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2023 Document type: Article Affiliation country: Japón