RNA sTructure prediction using IP Scheme

• Home
• IPknot++
• RactIP
• IPknot

Overview

The Rtips web server provides services for predicting RNA complicated secondary structures of given sequences, including intramolecular pseudoknots and joint structures formed from two RNAs. The programs in Rtips run fast and predict the maximum expected accuracy (MEA) structure using integer programming (IP). Let's get started by moving to respective services IPknot and RactIP.

Web Services

• IPknot++: RNA secondary structure prediction including pseudoknots for long sequences
• RactIP: RNA-RNA interaction (joint secondary structure) prediction
• IPknot: RNA secondary structure prediction including pseudoknots (old version)

Downloads

The C++ source codes are available for standalone use. In addition, the Perl template programs are provided to access several of the web services and parse the output.

• IPknot: Integer Programming-based prediction of RNA pseudoKNOTs
  • Source codes
  • Template program
• RactIP: RNA-RNA interACTion prediction using Integer Programming
  • Source codes
  • Template program

Note: If you try to run the programs continuously on a large dataset, we strongly recommend that you use the C++ standalone programs instead of the Perl programs to reduce the load on the server.

References

If you find Rtips useful, please cite the following article:

• Y. Kato, K. Sato, K. Asai and T. Akutsu, Rtips: fast and accurate tools for RNA 2D structure prediction using integer programming, Nucleic Acids Res., 40, W29-W34, 2012. [PubMed]
• K. Sato, Y. Kato, Prediction of RNA secondary structure including pseudoknots for long sequences, Briefings in Bioinformatics, 23(1):bbab395, 2022. [PubMed]
• K. Sato, Y. Kato, M. Hamada, T. Akutsu, K. Asai, IPknot: Fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming, Bioinformatics, 27, i85-93, 2011. [PubMed]
• Y. Kato, T. Mori K. Sato, S. Maegawa, H. Hosokawa and T. Akutsu, An accessibility-incorporated method for accurate prediction of RNA-RNA interactions from sequence data, Bioinformatics, 33, 202–209, 2017. [PubMed]
• Y. Kato, K. Sato, M. Hamada, Y. Watanabe, K. Asai, T. Akutsu, RactIP: Fast and accurate prediction of RNA-RNA interaction using integer programming, Bioinformatics, 26, i460-466, 2010. [PubMed]

Related references are also found in the help page of each tool.

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If you have any questions, please contact Yuki Kato, Kengo Sato.

Graduate School of Medicine, Osaka University, Japan
School of System Design and Technology, Tokyo Denki University, Japan