Evidence map›Paper›PMID 25838465›Full record

ArticleBioinformatics (Oxford, England)2015

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics.

Sebastian Will, Christina Otto, Milad Miladi, Mathias Möhl, Rolf Backofen

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. LocARNA 2.0: Versatile Simultaneous Alignment and Folding of RNAs.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  5. Article
  6. Network-Based Structural Alignment of RNA Sequences Using TOPAS.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. The locality dilemma of Sankoff-like RNA alignments.Bioinformatics (Oxford, England) · 2020
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Sebastian WillBioinformatics, Department of Computer Science, University of Freiburg, Freiburg, Germany, Bioinformatics, Department of Computer Science, University of Leipzig, Leipzig, Germany.
Christina OttoBioinformatics, Department of Computer Science, University of Freiburg, Freiburg, Germany.
Milad MiladiBioinformatics, Department of Computer Science, University of Freiburg, Freiburg, Germany.
Mathias MöhlBioinformatics, Department of Computer Science, University of Freiburg, Freiburg, Germany.
Rolf BackofenBioinformatics, Department of Computer Science, University of Freiburg, Freiburg, Germany, Centre for Biological Systems Analysis (ZBSA), University of Freiburg, Freiburg, Germany, Centre for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen, Denmark and Centre for Biological Signalling Studies (BIOSS), University of Freiburg, Freiburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationRNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of [Formula: see text]. Subsequently, numerous faster 'Sankoff-style' approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity ([Formula: see text] quartic time).

resultsBreaking this barrier, we introduce the novel Sankoff-style algorithm 'sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)', which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff's original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics.

Indexed as

AlgorithmsRNA FoldingHeuristicsSequence AlignmentSequence Analysis, RNA

Identifiers

PMID25838465
PMCPMC4514930

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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.