Evidence map›Paper›PMID 33973215›Full record

ArticleAdvances in experimental medicine and biology2021

Retrieval and Investigation of Data on SARS-CoV-2 and COVID-19 Using Bioinformatics Approach.

Muhamad Fahmi, Viol Dhea Kharisma, Arif Nur Muhammad Ansori, Masahiro Ito

Abstract read
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In one paragraph

Article in Advances in experimental medicine and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  3. Promising roles ofJournal of agriculture and food research · 2023
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  7. 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

4 authors.

Muhamad FahmiAdvanced Life Sciences Program, Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Shiga, Japan.
Viol Dhea KharismaMaster Program in Biology, Department of Biology, Faculty of Mathematic and Natural Sciences, Universitas Brawijaya, Malang, Indonesia.
Arif Nur Muhammad AnsoriDoctoral Program in Veterinary Science, Faculty of Veterinary Medicine, Universitas Airlangga, Kampus C Universitas Airlangga, Surabaya, Indonesia.
Masahiro ItoAdvanced Life Sciences Program, Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Shiga, Japan. maito@sk.ritsumei.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sudden emergence and a rapid outbreak of SARS-CoV-2 accompanied by a devastating impact on the economy and public health has driven extensive scientific mobilization to study and elucidate the various associated concerns about SARS-CoV-2. Bioinformatics plays a crucial role in addressing and providing solutions to questions about SARS-CoV-2. It helps shorten the duration for the vaccine development process and the discovery of potential clinical interventions through the simulation and information retrieval, and the development of well-ordered information hubs and resources, which are essential to derive data and meaningful findings from the current massive information about SARS-CoV-2. Advanced algorithms in this field also provide approaches that are essential to elucidate the relationship, origin, and evolutionary process of SARS-CoV-2. Here, we report essential bioinformatics entities, such as database and platform development, molecular evolution and phylogenetic analyses, and vaccine designs, that are useful to solve the SARS-CoV-2 conundrum.

Indexed as

COVID-19SARS-CoV-2Computational BiologyComputer SimulationHumansPhylogenyCOVID-19DatabasesInformation hubsMolecular evolutionPhylogenetic inferenceSARS-CoV-2Vaccine design

Identifiers

PMID33973215

What OpenQuestion holds

Textmetadata
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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.