Bioinformatics Goes Viral: I. Databases, Phylogenetics and Phylodynamics Tools for Boosting Virus Research.

bio-databases bioinformatics computational biology data mining phylodynamics phylogenetics sequence alignment virus evolution virus–host interaction

Journal

Viruses
ISSN: 1999-4915
Titre abrégé: Viruses
Pays: Switzerland
ID NLM: 101509722

Informations de publication

Date de publication:
06 Sep 2024
Historique:
received: 04 06 2024
revised: 21 08 2024
accepted: 03 09 2024
medline: 29 9 2024
pubmed: 28 9 2024
entrez: 28 9 2024
Statut: epublish

Résumé

Computer-aided analysis of proteins or nucleic acids seems like a matter of course nowadays; however, the history of Bioinformatics and Computational Biology is quite recent. The advent of high-throughput sequencing has led to the production of "big data", which has also affected the field of virology. The collaboration between the communities of bioinformaticians and virologists already started a few decades ago and it was strongly enhanced by the recent SARS-CoV-2 pandemics. In this article, which is the first in a series on how bioinformatics can enhance virus research, we show that highly useful information is retrievable from selected general and dedicated databases. Indeed, an enormous amount of information-both in terms of nucleotide/protein sequences and their annotation-is deposited in the general databases of international organisations participating in the International Nucleotide Sequence Database Collaboration (INSDC). However, more and more virus-specific databases have been established and are progressively enriched with the contents and features reported in this article. Since viruses are intracellular obligate parasites, a special focus is given to host-pathogen protein-protein interaction databases. Finally, we illustrate several phylogenetic and phylodynamic tools, combining information on algorithms and features with practical information on how to use them and case studies that validate their usefulness. Databases and tools for functional inference will be covered in the next article of this series:

Identifiants

pubmed: 39339901
pii: v16091425
doi: 10.3390/v16091425
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Federico Vello (F)

Synthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, 35131 Padua, Italy.

Francesco Filippini (F)

Synthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, 35131 Padua, Italy.

Irene Righetto (I)

Synthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, 35131 Padua, Italy.

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Classifications MeSH