Evidence map›Paper›PMID 26335276›Full record

ArticleBMC bioinformatics2015

Multi-objective optimization for RNA design with multiple target secondary structures.

Akito Taneda

Abstract read
In one paragraph

Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

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13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Riboswitch Design Using MODENA.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  4. Article
  5. Article
  6. The energy-spectrum of bicompatible sequences.Algorithms for molecular biology : AMB · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Akito TanedaGraduate School of Science and Technology, Hirosaki University, 3 Bunkyo-cho, Hirosaki, Aomori, Japan. taneda@eit.hirosaki-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRNAs are attractive molecules as the biological parts for synthetic biology. In particular, the ability of conformational changes, which can be encoded in designer RNAs, enables us to create multistable molecular switches that function in biological circuits. Although various algorithms for designing such RNA switches have been proposed, the previous algorithms optimize the RNA sequences against the weighted sum of objective functions, where empirical weights among objective functions are used. In addition, an RNA design algorithm for multiple pseudoknot targets is currently not available.

resultsWe developed a novel computational tool for automatically designing RNA sequences which fold into multiple target secondary structures. Our algorithm designs RNA sequences based on multi-objective genetic algorithm, by which we can explore the RNA sequences having good objective function values without empirical weight parameters among the objective functions. Our algorithm has great flexibility by virtue of this weight-free nature. We benchmarked our multi-target RNA design algorithm with the datasets of two, three, and four target structures and found that our algorithm shows better or comparable design performances compared with the previous algorithms, RNAdesign and Frnakenstein. In addition to the benchmarks with pseudoknot-free datasets, we benchmarked MODENA with two-target pseudoknot datasets and found that MODENA can design the RNAs which have the target pseudoknotted secondary structures whose free energies are close to the lowest free energy. Moreover, we applied our algorithm to a ribozyme-based ON-switch which takes a ribozyme-inactive secondary structure when the theophylline aptamer structure is assumed.

conclusionsCurrently, MODENA is the only RNA design software which can be applied to multiple pseudoknot targets. Successful design results for the multiple targets and an RNA device indicate usefulness of our multi-objective RNA design algorithm.

Indexed as

AlgorithmsBase SequenceNucleic Acid ConformationProtein Structure, SecondaryRNASequence Analysis, RNARNA

Identifiers

PMID26335276
PMCPMC4559319

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.