Evidence map›Paper›PMID 33421654›Full record

ReviewInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2021

Topological Analysis for Sequence Variability: Case Study on more than 2K SARS-CoV-2 sequences of COVID-19 infected 54 countries in comparison with SARS-CoV-1 and MERS-CoV.

Jnanendra Prasad Sarkar, Indrajit Saha, Arijit Seal, Debasree Maity, Ujjwal Maulik

Abstract readReview
In one paragraph

Review in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

5 authors.

Jnanendra Prasad SarkarLarsen & Toubro Infotech Ltd., Pune, Maharashtra, India; Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India.
Indrajit SahaDepartment of Computer Science and Engineering, National Institute of Technical Teachers' Training & Research, Kolkata, West Bengal, India. Electronic address: indrajit@nitttrkol.ac.in.
Arijit SealCognizant Technology Solutions, Kolkata, West Bengal, India.
Debasree MaityDepartment of Electronics and Communication Engineering, MCKV Institute of Engineering, Howrah, West Bengal, India.
Ujjwal MaulikDepartment of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pandemic due to novel coronavirus, SARS-CoV-2 is a serious global concern now. More than thousand new COVID-19 infections are getting reported daily for this virus across the globe. Thus, the medical research communities are trying to find the remedy to restrict the spreading of this virus, while the vaccine development work is still under research in parallel. In such critical situation, not only the medical research community, but also the scientists in different fields like microbiology, pharmacy, bioinformatics and data science are also sharing effort to accelerate the process of vaccine development, virus prediction, forecasting the transmissible probability and reproduction cases of virus for social awareness. With the similar context, in this article, we have studied sequence variability of the virus primarily focusing on three aspects: (a) sequence variability among SARS-CoV-1, MERS-CoV and SARS-CoV-2 in human host, which are in the same coronavirus family, (b) sequence variability of SARS-CoV-2 in human host for 54 different countries and (c) sequence variability between coronavirus family and country specific SARS-CoV-2 sequences in human host. For this purpose, as a case study, we have performed topological analysis of 2391 global genomic sequences of SARS-CoV-2 in association with SARS-CoV-1 and MERS-CoV using an integrated semi-alignment based computational technique. The results of the semi-alignment based technique are experimentally and statistically found similar to alignment based technique and computationally faster. Moreover, the outcome of this analysis can help to identify the nations with homogeneous SARS-CoV-2 sequences, so that same vaccine can be applied to their heterogeneous human population.

Indexed as

Genetic VariationGenome, ViralPandemicsAfricaAmericasAsiaAustraliaBase SequenceComputational BiologyCoronavirus InfectionsCOVID-19EuropeHost-Pathogen InteractionsHumansMiddle East Respiratory Syndrome CoronavirusSARS-CoV-2CoronavirsusCOVID-19Genomic sequencesGlobal healthMERS-CoVSARS-CoV-2Sequence alignment free technique

Identifiers

PMID33421654
PMCPMC7787073

What OpenQuestion holds

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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.