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Microorganisms
Special Issues
Bioinformatics Research on Viruses
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Bioinformatics Research on Viruses

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Virology".

Deadline for manuscript submissions: closed (31 July 2025) | Viewed by 241

Special Issue Editors

Prof. Dr. Manja Marz

E-Mail Website
Guest Editor
Leibniz Institute on Aging—Fritz Lipmann Institute, Jena, Germany
Interests: aging
Dr. Paula Istvan

E-Mail Website
Guest Editor
European Virus Bioinformatics Center, Friedrich Schiller University Jena, Jena, Germany
Interests: high throughput sequencing analysis; bioinformatic analysis; algorithmic bioinformatics; microbiome

Special Issue Information

Dear Colleagues,

The “Bioinformatics Research on Viruses” Special Issue highlights the transformative impact of computational biology on understanding viral complexity in the modern era. With viruses representing both a global health challenge and a biological enigma, this Special Issue seeks contributions that utilize bioinformatics to decode viral mechanisms, evolution, and interactions with hosts. Key areas of interest include the design of innovative algorithms for high-throughput viral genome analysis, the elucidation of viral–host co-evolutionary dynamics, and the prediction of viral behaviors under environmental and therapeutic pressures. This Special Issue also encourages submissions that explore the role of artificial intelligence and machine learning in virology, providing new avenues for surveillance, vaccine design, and antiviral drug development. By fostering an intersection of virology and computational sciences, this Special Issue aims to inspire cutting-edge discoveries and practical applications in viral research.

Prof. Dr. Manja Marz
Dr. Paula Istvan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Microorganisms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • viral bioinformatics
  • genomic epidemiology
  • virus–host co-evolution
  • AI in virology
  • high-throughput sequencing
  • viral dynamics
  • therapeutic bioinformatics
  • computational virology tools
  • emerging viral threats
  • systems virology

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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Research

15 pages, 313 KB  
Article
Viral Quasispecies Inference from Single Observations—Mutagens as Accelerators of Quasispecies Evolution
by Josep Gregori, Miquel Salicrú, Marta Ibáñez-Lligoña, Sergi Colomer-Castell, Carolina Campos, Alvaro González-Camuesco and Josep Quer
Microorganisms 2025, 13(9), 2029; https://doi.org/10.3390/microorganisms13092029 (registering DOI) - 30 Aug 2025
Abstract
RNA virus populations exist as quasispecies-complex, dynamic clouds of closely related but genetically diverse variants generated by high mutation rates during replication. Assessing quasispecies structure and diversity is crucial for understanding viral evolution, adaptation, and response to antiviral treatments. However, comparing single quasispecies [...] Read more.
RNA virus populations exist as quasispecies-complex, dynamic clouds of closely related but genetically diverse variants generated by high mutation rates during replication. Assessing quasispecies structure and diversity is crucial for understanding viral evolution, adaptation, and response to antiviral treatments. However, comparing single quasispecies observations from individual biosamples, especially at different infection or treatment time points, presents statistical challenges. Traditional inferential tests are inapplicable due to the lack of replicate observations, and resampling-based approaches such as the bootstrap and jackknife are limited by biases and non-independence, particularly for diversity indices sensitive to rare haplotypes. In this study, we address these limitations by applying the delta method to derive analytical variances for a set of quasispecies structure indicators specifically designed to assess the quasispecies maturation state. We demonstrate the utility of this approach using high-depth next-generation sequencing data from hepatitis C virus (HCV) quasispecies evolving in vitro under various conditions, including free evolution and exposure to antiviral or mutagenic treatments. Our results reveal that with highly fit HCV quasispecies, sofosbuvir inhibits quasispecies genetic diversity, while mutagenic treatments accelerate maturation, compared to untreated controls. We emphasize the interpretation of results through absolute differences, log-fold changes, and standardized effect sizes, moving beyond mere statistical significance. This framework enables robust, quantitative comparisons of quasispecies diversity from single observations, providing valuable insights into viral adaptation and treatment response. The R code and session info with required libraries and versions is provided in the supplementary material. Full article
(This article belongs to the Special Issue Bioinformatics Research on Viruses)
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