-
Je něco špatně v tomto záznamu ?
Recent trends on omics and bioinformatics approaches to study SARS-CoV-2: A bibliometric analysis and mini-review
J. Murillo, LM. Villegas, LM. Ulloa-Murillo, AR. Rodríguez
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články, přehledy
NLK
ProQuest Central
od 2003-01-01 do 2023-12-31
Nursing & Allied Health Database (ProQuest)
od 2003-01-01 do 2023-12-31
Health & Medicine (ProQuest)
od 2003-01-01 do 2023-12-31
- MeSH
- bibliometrie * MeSH
- COVID-19 * epidemiologie genetika metabolismus MeSH
- fylogeneze * MeSH
- lidé MeSH
- pandemie * MeSH
- SARS-CoV-2 * genetika metabolismus MeSH
- simulace molekulového dockingu MeSH
- výpočetní biologie * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
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.
Citace poskytuje Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc21011646
- 003
- CZ-PrNML
- 005
- 20210507101946.0
- 007
- ta
- 008
- 210420s2021 xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1016/j.compbiomed.2020.104162 $2 doi
- 035 __
- $a (PubMed)33310371
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Murillo, Julieth $u Faculty of Engineering, Pontificia Universidad Javeriana-Cali, Cali, Colombia. Electronic address: juliethmurillo@javerianacali.edu.co
- 245 10
- $a Recent trends on omics and bioinformatics approaches to study SARS-CoV-2: A bibliometric analysis and mini-review / $c J. Murillo, LM. Villegas, LM. Ulloa-Murillo, AR. Rodríguez
- 520 9_
- $a 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.
- 650 12
- $a bibliometrie $7 D015706
- 650 12
- $a COVID-19 $x epidemiologie $x genetika $x metabolismus $7 D000086382
- 650 12
- $a výpočetní biologie $7 D019295
- 650 _2
- $a lidé $7 D006801
- 650 _2
- $a simulace molekulového dockingu $7 D062105
- 650 12
- $a pandemie $7 D058873
- 650 12
- $a fylogeneze $7 D010802
- 650 12
- $a SARS-CoV-2 $x genetika $x metabolismus $7 D000086402
- 655 _2
- $a časopisecké články $7 D016428
- 655 _2
- $a přehledy $7 D016454
- 700 1_
- $a Villegas, Lina María $u Faculty of Health, Universidad Del Valle, Cali, Colombia. Electronic address: lina.villegas@correounivalle.edu.co
- 700 1_
- $a Ulloa-Murillo, Leidy Marcela $u Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Czech Republic. Electronic address: ulloa_murillo@af.czu.cz
- 700 1_
- $a Rodríguez, Alejandra Rocío $u Faculty of Health, Universidad Del Valle, Cali, Colombia. Electronic address: alejandra.rodriguez@correounivalle.edu.co
- 773 0_
- $w MED00001218 $t Computers in biology and medicine $x 1879-0534 $g Roč. 128, č. - (2021), s. 104162
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/33310371 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y p $z 0
- 990 __
- $a 20210420 $b ABA008
- 991 __
- $a 20210507101945 $b ABA008
- 999 __
- $a ok $b bmc $g 1650114 $s 1132025
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2021 $b 128 $c - $d 104162 $e 20201203 $i 1879-0534 $m Computers in biology and medicine $n Comput Biol Med $x MED00001218
- LZP __
- $a Pubmed-20210420