Evidence map›Paper›PMID 28974235›Full record

ReviewGenome biology2017

Alignment-free sequence comparison: benefits, applications, and tools.

Andrzej Zielezinski, Susana Vinga, Jonas Almeida, Wojciech M Karlowski

Abstract readReview
In one paragraph

Review in Genome biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 236 papers.

0numbers the graph read from it
0cells of the map it votes in
236citing 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

236 citing papers in PubMed.

  1. Article
  2. Alignment-freeJournal of clinical microbiology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Estimation of substitution and indel rates via k-mer statistics.Algorithms for molecular biology : AMB · 2026
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. The gift of novelty: repeat-robustbioRxiv : the preprint server for biology · 2026
    Article
  13. Article
  14. Alignment-Free Guided Design of a Pan-Orthoflavivirus RT-qPCR Assay.bioRxiv : the preprint server for biology · 2026
    Article
  15. GenCore: Genomic distance estimation using Locally Consistent Parsing.bioRxiv : the preprint server for biology · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

176 more citing papers are in PubMed but not listed here.

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

4 authors.

Andrzej ZielezinskiDepartment of Computational Biology, Faculty of Biology, Adam Mickiewicz University in Poznan, Umultowska 89, 61-614, Poznan, Poland.
Susana VingaIDMEC, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001, Lisbon, Portugal.
Jonas AlmeidaStony Brook University (SUNY), 101 Nicolls Road, Stony Brook, NY, 11794, USA.
Wojciech M KarlowskiDepartment of Computational Biology, Faculty of Biology, Adam Mickiewicz University in Poznan, Umultowska 89, 61-614, Poznan, Poland. wmk@amu.edu.pl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alignment-free sequence analyses have been applied to problems ranging from whole-genome phylogeny to the classification of protein families, identification of horizontally transferred genes, and detection of recombined sequences. The strength of these methods makes them particularly useful for next-generation sequencing data processing and analysis. However, many researchers are unclear about how these methods work, how they compare to alignment-based methods, and what their potential is for use for their research. We address these questions and provide a guide to the currently available alignment-free sequence analysis tools.

Indexed as

AlgorithmsHigh-Throughput Nucleotide SequencingInformation TheorySequence AlignmentSequence AnalysisSequence HomologySoftware

Identifiers

PMID28974235
PMCPMC5627421

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.