Evidence map›Paper›PMID 24267034›Full record

ArticleBMC bioinformatics2013

Classification of genomic signals using dynamic time warping.

Helena Skutkova, Martin Vitek, Petr Babula, Rene Kizek, Ivo Provaznik

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Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Review
  2. Peak Persistence Diagrams for Shape-Based Signal Estimation.IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society · 2025
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  3. Data-driven classification of ligand unbinding pathways.Proceedings of the National Academy of Sciences of the United States of America · 2024
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  11. A degeneration-reducing criterion for optimal digital mapping of genetic codes.Computational and structural biotechnology journal · 2019
    Article
  12. Article
  13. Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Helena Skutkova
Martin Vitek
Petr Babula
Rene Kizek
Ivo Provaznik

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClassification methods of DNA most commonly use comparison of the differences in DNA symbolic records, which requires the global multiple sequence alignment. This solution is often inappropriate, causing a number of imprecisions and requires additional user intervention for exact alignment of the similar segments. The similar segments in DNA represented as a signal are characterized by a similar shape of the curve. The DNA alignment in genomic signals may adjust whole sections not only individual symbols. The dynamic time warping (DTW) is suitable for this purpose and can replace the multiple alignment of symbolic sequences in applications, such as phylogenetic analysis.

methodsThe proposed method is composed of three main parts. The first part represent conversion of symbolic representation of DNA sequences in the form of a string of A,C,G,T symbols to signal representation in the form of cumulated phase of complex components defined for each symbol. Next part represents signals size adjustment realized by standard signal preprocessing methods: median filtration, detrendization and resampling. The final part necessary for genomic signals comparison is position and length alignment of genomic signals by dynamic time warping (DTW).

resultsThe application of the DTW on set of genomic signals was evaluated in dendrogram construction using cluster analysis. The resulting tree was compared with a classical phylogenetic tree reconstructed using multiple alignment. The classification of genomic signals using the DTW is evolutionary closer to phylogeny of organisms. This method is more resistant to errors in the sequences and less dependent on the number of input sequences.

conclusionsClassification of genomic signals using dynamic time warping is an adequate variant to phylogenetic analysis using the symbolic DNA sequences alignment; in addition, it is robust, quick and more precise technique.

Indexed as

ActinsAnimalsBase SequenceBiological EvolutionChickensGenetic PhenomenaGenomicsHumansMacaca mulattaMolecular Dynamics SimulationPhylogenySequence AlignmentSignal TransductionTime FactorsActins

Identifiers

PMID24267034
PMCPMC3750471

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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.