Evidence map›Paper›PMID 31312019›Full record

ArticleScientific reports2019

Ultra-fast genome comparison for large-scale genomic experiments.

Esteban Pérez-Wohlfeil, Sergio Diaz-Del-Pino, Oswaldo Trelles

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  5. Article
  6. Genome sequence assembly and annotation ofNAR genomics and bioinformatics · 2025
    Article
  7. Article
  8. Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Identification ofFrontiers in veterinary science · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Article
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  18. Review
  19. Article
  20. 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

3 authors.

Esteban Pérez-WohlfeilComputer Architecture Department, University of Málaga - Instituto de Investigación Biomédica de Málaga-IBIMA, Málaga, Spain.ORCID http://orcid.org/0000-0002-3572-686X
Sergio Diaz-Del-PinoComputer Architecture Department, University of Málaga - Instituto de Investigación Biomédica de Málaga-IBIMA, Málaga, Spain.
Oswaldo TrellesComputer Architecture Department, University of Málaga - Instituto de Investigación Biomédica de Málaga-IBIMA, Málaga, Spain. ortrelles@uma.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last decade, a technological shift in the bioinformatics field has occurred: larger genomes can now be sequenced quickly and cost effectively, resulting in the computational need to efficiently compare large and abundant sequences. Furthermore, detecting conserved similarities across large collections of genomes remains a problem. The size of chromosomes, along with the substantial amount of noise and number of repeats found in DNA sequences (particularly in mammals and plants), leads to a scenario where executing and waiting for complete outputs is both time and resource consuming. Filtering steps, manual examination and annotation, very long execution times and a high demand for computational resources represent a few of the many difficulties faced in large genome comparisons. In this work, we provide a method designed for comparisons of considerable amounts of very long sequences that employs a heuristic algorithm capable of separating noise and repeats from conserved fragments in pairwise genomic comparisons. We provide software implementation that computes in linear time using one core as a minimum and a small, constant memory footprint. The method produces both a previsualization of the comparison and a collection of indices to drastically reduce computational complexity when performing exhaustive comparisons. Last, the method scores the comparison to automate classification of sequences and produces a list of detected synteny blocks to enable new evolutionary studies.

Indexed as

GenomeAlgorithmsAnimalsBiological EvolutionData VisualizationGenomicsHumansMammalsMicePoaceaeSoftwareSyntenyTime FactorsTriticum

Identifiers

PMID31312019
PMCPMC6635410

What OpenQuestion holds

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Registered trials

None linked

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.