Evidence map›Paper›PMID 32827671›Full record

ArticleGenomics2020

A new graph-theoretic approach to determine the similarity of genome sequences based on nucleotide triplets.

Subhram Das, Arijit Das, D K Bhattacharya, D N Tibarewala

Abstract read
In one paragraph

Article in Genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Overview and Prospects of DNA Sequence Visualization.International journal of molecular sciences · 2025
    Review
  5. Article
  6. Review
  7. Article
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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.

Subhram DasComputer Science and Engineering, Narula Institute of Technology, Kolkata 700109, India. Electronic address: subhram.das@nit.ac.in.
Arijit DasComputer Science and Engineering, Narula Institute of Technology, Kolkata 700109, India.
D K BhattacharyaPure Mathematics, Calcutta University, Kolkata 700019, India.
D N TibarewalaBio-Science and Engineering, Jadavpur University, Kolkata 700032, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Methods of finding sequence similarity play a significant role in computational biology. Owing to the rapid increase of genome sequences in public databases, the evolutionary relationship of species becomes more challenging. But traditional alignment-based methods are found inappropriate due to their time-consuming nature. Therefore, it is necessary to find a faster method, which applies to species phylogeny. In this paper, a new graph-theory based alignment-free sequence comparison method is proposed. A complete-bipartite graph is used to represent each genome sequence based on its nucleotide triplets. Subsequently, with the help of the weights of edges of the graph, a vector descriptor is formed. Finally, the phylogenetic tree is drawn using the UPGMA algorithm. In the present case, the datasets for comparison are related to mammals, viruses, and bacteria. In most of the cases, the phylogeny in the present case is found to be more satisfactory as compared to earlier methods.

Indexed as

Computational BiologyAlgorithmsAnimalsBacteriaMammalsNucleotidesPhylogenySequence Analysis, DNAVirusesNucleotidesAlignment-based methodAlignment-free methodBipartite graphEvolutionary relationshipPhylogenetic treeSequence comparison

Identifiers

PMID32827671
PMCPMC7437474

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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.