Evidence map›Paper›PMID 16144519›Full record

ArticleGenomics, proteomics & bioinformatics2005

SARS-CoV genome polymorphism: a bioinformatics study.

Gordana M Pavlović-Lazetić, Nenad S Mitić, Andrija M Tomović, Mirjana D Pavlović, Milos V Beljanski

Abstract readComparative Study
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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.

Gordana M Pavlović-LazetićFaculty of Mathematics, University of Belgrade, 11001 Belgrade, Serbia and Montenegro. gordana@matf.bg.ac.yu
Nenad S Mitić
Andrija M Tomović
Mirjana D Pavlović
Milos V Beljanski

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A dataset of 103 SARS-CoV isolates (101 human patients and 2 palm civets) was investigated on different aspects of genome polymorphism and isolate classification. The number and the distribution of single nucleotide variations (SNVs) and insertions and deletions, with respect to a "profile", were determined and discussed ("profile" being a sequence containing the most represented letter per position). Distribution of substitution categories per codon positions, as well as synonymous and non-synonymous substitutions in coding regions of annotated isolates, was determined, along with amino acid (a.a.) property changes. Similar analysis was performed for the spike (S) protein in all the isolates (55 of them being predicted for the first time). The ratio Ka/Ks confirmed that the S gene was subjected to the Darwinian selection during virus transmission from animals to humans. Isolates from the dataset were classified according to genome polymorphism and genotypes. Genome polymorphism yields to two groups, one with a small number of SNVs and another with a large number of SNVs, with up to four subgroups with respect to insertions and deletions. We identified three basic nine-locus genotypes: TTTT/TTCGG, CGCC/TTCAT, and TGCC/TTCGT, with four subgenotypes. Both classifications proposed are in accordance with the new insights into possible epidemiological spread, both in space and time.

Indexed as

Computational BiologyGenetic VariationGenomeAmino Acid SequenceAnimalsHumansMolecular Sequence DataMutationPhylogenyPolymorphism, GeneticSequence DeletionSequence Homology, Amino AcidSevere Acute Respiratory SyndromeSevere acute respiratory syndrome-related coronavirusTaiwanViverridae

Identifiers

PMID16144519
PMCPMC5172477

What OpenQuestion holds

Textmetadata
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.