Evidence map›Paper›PMID 21399690›Full record

ArticlePloS one2011

A novel method of characterizing genetic sequences: genome space with biological distance and applications.

Mo Deng, Chenglong Yu, Qian Liang, Rong L He, Stephen S-T Yau

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 citing papers in PubMed.

  1. Trial
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  7. Article
  8. The optimal metric for viral genome space.Computational and structural biotechnology journal · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Unsupervised identification of significant lineages of SARS-CoV-2 through scalable machine learning methods.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
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  19. Article
  20. In-depth investigation of the point mutation pattern of HIV-1.Frontiers in cellular and infection microbiology · 2022
    Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

5 authors.

Mo DengDepartment of Mathematics, Statistics and Computer Science, University of Illinois at Chicago, Chicago, Illinois, United States of America.
Chenglong Yu
Qian Liang
Rong L He
Stephen S-T Yau

Funding

Role of serum amyloid A in interferon-gamma expression and T helper 1 cell differSC3GM098180 · NIGMS · CHICAGO STATE UNIVERSITY · PI HE, RONG LUCY · 2011 to 2014
$431k
NIGMS NIH HHS SC3 GM098180
6 · The paper itself

Abstract

backgroundMost existing methods for phylogenetic analysis involve developing an evolutionary model and then using some type of computational algorithm to perform multiple sequence alignment. There are two problems with this approach: (1) different evolutionary models can lead to different results, and (2) the computation time required for multiple alignments makes it impossible to analyse the phylogeny of a whole genome. This motivates us to create a new approach to characterize genetic sequences. METHODOLOGY: To each DNA sequence, we associate a natural vector based on the distributions of nucleotides. This produces a one-to-one correspondence between the DNA sequence and its natural vector. We define the distance between two DNA sequences to be the distance between their associated natural vectors. This creates a genome space with a biological distance which makes global comparison of genomes with same topology possible. We use our proposed method to analyze the genomes of the new influenza A (H1N1) virus, human rhinoviruses (HRV) and mammalian mitochondrial. The result shows that a triple-reassortant swine virus circulating in North America and the Eurasian swine virus belong to the lineage of the influenza A (H1N1) virus. For the HRV and mammalian mitochondrial genomes, the results coincide with biologists' analyses.

conclusionsOur approach provides a powerful new tool for analyzing and annotating genomes and their phylogenetic relationships. Whole or partial genomes can be handled more easily and more quickly than using multiple alignment methods. Once a genome space has been constructed, it can be stored in a database. There is no need to reconstruct the genome space for subsequent applications, whereas in multiple alignment methods, realignment is needed to add new sequences. Furthermore, one can make a global comparison of all genomes simultaneously, which no other existing method can achieve.

Indexed as

AnimalsBase SequenceCluster AnalysisGenetic VectorsGenomeGenome, MitochondrialGenome, ViralHumansInfluenza A Virus, H1N1 SubtypeMammalsPhylogenySequence Analysis, DNA

Identifiers

PMID21399690
PMCPMC3047556

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Registered trials

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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.