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Distance Profiles of Optimal RNA Foldings

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Bioinformatics Research and Applications (ISBRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 13760))

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Abstract

Predicting the secondary structure of RNA is an important problem in molecular biology, providing insights into the function of non-coding Rn As and with broad applications in understanding disease, the development of new drugs, among others. Combinatorial algorithms for predicting RNA foldings can generate an exponentially large number of equally optimal foldings with respect to a given optimization criterion, making it difficult to determine how well any single folding represents the entire space. We provide efficient new algorithms for providing insights into this large space of optimal RNA foldings and a research software tool, toRNAdo, that implements these algorithms.

This work was funded by the U.S. National Science Foundation under Grant Number IIS-1419739 to Claremont McKenna College.

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Notes

  1. 1.

    WM is the multiloop DP table [14] and table \({\textbf {WM2}}\) is introduced here as a “helper” table that allows us to avoid double-counting optimal solutions involving multiloops.

  2. 2.

    A common heuristic bounds the interior loop size, which reduces the running time to \(O(n^3)\).

  3. 3.

    Our implementation of the convolution operator in the accompanying toRNAdo software tool is not optimized and uses the naive \(O(n^2)\) algorithm.

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Acknowledgements

The authors thank Harvey Mudd College for use of lab resources and the four anonymous reviewers for valuable feedback and suggestions.

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Authors and Affiliations

  1. Department of Computer Science, Harvey Mudd College, Claremont, USA

    J. Liu, I. Duan & S. Santichaivekin

  2. Kravis Department of Integrated Sciences, Claremont McKenna College Claremont, Claremont, CA, 91711, USA

    R. Libeskind-Hadas

Authors
  1. J. Liu
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  2. I. Duan
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  3. S. Santichaivekin
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  4. R. Libeskind-Hadas
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Corresponding author

Correspondence to R. Libeskind-Hadas .

Editor information

Editors and Affiliations

  1. University of Connecticut, Storrs, CT, USA

    Mukul S. Bansal

  2. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

  3. University of Southern California, Los Angeles, CA, USA

    Serghei Mangul

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Liu, J., Duan, I., Santichaivekin, S., Libeskind-Hadas, R. (2022). Distance Profiles of Optimal RNA Foldings. In: Bansal, M.S., Cai, Z., Mangul, S. (eds) Bioinformatics Research and Applications. ISBRA 2022. Lecture Notes in Computer Science(), vol 13760. Springer, Cham. https://doi.org/10.1007/978-3-031-23198-8_29

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  • DOI: https://doi.org/10.1007/978-3-031-23198-8_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23197-1

  • Online ISBN: 978-3-031-23198-8

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