Evidence map›Paper›PMID 31828235›Full record

ArticleAnnual review of biomedical data science2018

Alignment-Free Sequence Analysis and Applications.

Jie Ren, Xin Bai, Yang Young Lu, Kujin Tang, Ying Wang, Gesine Reinert, Fengzhu Sun

Abstract read
In one paragraph

Article in Annual review of biomedical data science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

  1. Alignment-freeJournal of clinical microbiology · 2026
    Article
  2. Article
  3. Article
  4. Alignment-Free Guided Design of a Pan-Orthoflavivirus RT-qPCR Assay.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Genome research · 2025
    Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. (Bioinformatics advances · 2023
    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

7 authors.

Jie RenMolecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA.
Xin BaiMolecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA.
Yang Young LuMolecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA.
Kujin TangMolecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA.
Ying WangDepartment of Automation, Xiamen University, Xiamen, Fujian, China.
Gesine ReinertDepartment of Statistics, University of Oxford, Oxford, United Kingdom.
Fengzhu SunMolecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA.

Funding

Computational Studies of Virus-host Interactions Using Metagenomics Data and ApplicationsR01GM120624 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI AHLGREN, NATHAN, SUN, FENGZHU · 2017 to 2020
$1.7M
NIGMS NIH HHS R01 GM120624
6 · The paper itself

Abstract

Genome and metagenome comparisons based on large amounts of next generation sequencing (NGS) data pose significant challenges for alignment-based approaches due to the huge data size and the relatively short length of the reads. Alignment-free approaches based on the counts of word patterns in NGS data do not depend on the complete genome and are generally computationally efficient. Thus, they contribute significantly to genome and metagenome comparison. Recently, novel statistical approaches have been developed for the comparison of both long and shotgun sequences. These approaches have been applied to many problems including the comparison of gene regulatory regions, genome sequences, metagenomes, binning contigs in metagenomic data, identification of virus-host interactions, and detection of horizontal gene transfers. We provide an updated review of these applications and other related developments of word-count based approaches for alignment-free sequence analysis.

Indexed as

alignmentalignment-freehorizontal gene transferMarkov chainmetagenomicsphylogenysequence comparisonvirus-host interaction

Identifiers

PMID31828235
PMCPMC6905628

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.