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10.1016/j.compbiomed.2020.104162

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suck abstract from ncbi


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pmid33310371      Comput+Biol+Med 2021 ; 128 (ä): 104162
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  • Recent trends on omics and bioinformatics approaches to study SARS-CoV-2: A bibliometric analysis and mini-review #MMPMID33310371
  • Murillo J; Villegas LM; Ulloa-Murillo LM; Rodriguez AR
  • Comput Biol Med 2021[Jan]; 128 (ä): 104162 PMID33310371show ga
  • BACKGROUND: The successful sequencing of SARS-CoV-2 cleared the way for the use of omics technologies and integrative biology research for combating the COVID-19 pandemic. Currently, many research groups have slowed down their respective projects to concentrate efforts in the study of the biology of SARS-CoV-2. In this bibliometric analysis and mini-review, we aimed to describe how computational methods or omics approaches were used during the first months of the COVID-19 pandemic. METHODS: We analyzed bibliometric data from Scopus, BioRxiv, and MedRxiv (dated June 19th, 2020) using quantitative and knowledge mapping approaches. We complemented our analysis with a manual process of carefully reading the selected articles to identify either the omics or bioinformatic tools used and their purpose. RESULTS: From a total of 184 articles, we found that metagenomics and transcriptomics were the main sources of data to perform phylogenetic analysis aimed at corroborating zoonotic transmission, identifying the animal origin and taxonomic allocation of SARS-CoV-2. Protein sequence analysis, immunoinformatics and molecular docking were used to give insights about SARS-CoV-2 targets for drug and vaccine development. Most of the publications were from China and USA. However, China, Italy and India covered the top 10 most cited papers on this topic. CONCLUSION: We found an abundance of publications using omics and bioinformatics approaches to establish the taxonomy and animal origin of SARS-CoV-2. We encourage the growing community of researchers to explore other lesser-known aspects of COVID-19 such as virus-host interactions and host response.
  • |*Bibliometrics[MESH]
  • |*COVID-19/epidemiology/genetics/metabolism[MESH]
  • |*Computational Biology[MESH]
  • |*Pandemics[MESH]
  • |*Phylogeny[MESH]
  • |*SARS-CoV-2/genetics/metabolism[MESH]
  • |Humans[MESH]


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