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Vaccines
Special Issues
Immunoinformatic Approaches to Vaccine Design
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Immunoinformatic Approaches to Vaccine Design

A special issue of Vaccines (ISSN 2076-393X). This special issue belongs to the section "Vaccination Optimization".

Deadline for manuscript submissions: closed (20 August 2023) | Viewed by 4409

Special Issue Editor

Dr. Amit Prasad

E-Mail Website
Guest Editor
Indian Institute of Technology Mandi, Mandi, India
Interests: role of innate immune cells in inflammatory disorders; host-pathogen interactions; medicinal plants of Himalayan region and their immune modulating capabilities; bio-sensors and medical devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

I am pleased to invite you to submit contributions (original research article, reviews, short communication, etc.) to a Special Issue focused on designs, improvements, and vaccination strategies for multi-epitope vaccines using an immunoinformatics approach. The evolution of AI, ML and neural network approaches in vaccine designs has changed the whole process of vaccine conceptualization and their production. Interestingly, today, we can even predict the chances of a candidate vaccine’s population coverage and efficacy. With regard to contributions to this Special Issue, full experimental details, including servers/software/data banks, must be provided so that the results can be reproduced, and any computed data or files regarding the full details of the experimental procedure can be deposited as supplementary materials. Please note that all bioinformatics/immunoinformatics papers are need experimental validation (in vitro or in vivo).

This Special Issue will feature articles related to computationally designed vaccines, system immunology, computational tools, and new approaches to boost vaccine efficacy. We will also welcome articles related to policy matter discussion regarding the use of the immunoinformatics in vaccine designs.

Dr. Amit Prasad
Guest Editor

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. Vaccines 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

  • multi-epitope
  • immunoinformatics
  • vaccine
  • antigens
  • inflammation

Published Papers (2 papers)

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Editorial

Jump to: Research

4 pages, 6614 KiB  
Editorial
Immunoinformatics Approaches for Vaccine Design: A Fast and Secure Strategy for Successful Vaccine Development
by Suraj Singh Rawat, Anand Kumar Keshri, Rimanpreet Kaur and Amit Prasad
Vaccines 2023, 11(2), 221; https://doi.org/10.3390/vaccines11020221 - 19 Jan 2023
Cited by 10 | Viewed by 2398
Abstract
Vaccines are major contributors to the cost-effective interventions in major infectious diseases in the global public health space [...] Full article
(This article belongs to the Special Issue Immunoinformatic Approaches to Vaccine Design)
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Research

Jump to: Editorial

19 pages, 4264 KiB  
Article
Multi-View Learning to Unravel the Different Levels Underlying Hepatitis B Vaccine Response
by Fabio Affaticati, Esther Bartholomeus, Kerry Mullan, Pierre Van Damme, Philippe Beutels, Benson Ogunjimi, Kris Laukens and Pieter Meysman
Vaccines 2023, 11(7), 1236; https://doi.org/10.3390/vaccines11071236 - 13 Jul 2023
Viewed by 1396
Abstract
The immune system acts as an intricate apparatus that is dedicated to mounting a defense and ensures host survival from microbial threats. To engage this faceted immune response and provide protection against infectious diseases, vaccinations are a critical tool to be developed. However, [...] Read more.
The immune system acts as an intricate apparatus that is dedicated to mounting a defense and ensures host survival from microbial threats. To engage this faceted immune response and provide protection against infectious diseases, vaccinations are a critical tool to be developed. However, vaccine responses are governed by levels that, when interrogated, separately only explain a fraction of the immune reaction. To address this knowledge gap, we conducted a feasibility study to determine if multi-view modeling could aid in gaining actionable insights on response markers shared across populations, capture the immune system’s diversity, and disentangle confounders. We thus sought to assess this multi-view modeling capacity on the responsiveness to the Hepatitis B virus (HBV) vaccination. Seroconversion to vaccine-induced antibodies against the HBV surface antigen (anti-HBs) in early converters (n = 21; <2 months) and late converters (n = 9; <6 months) and was defined based on the anti-HBs titers (>10IU/L). The multi-view data encompassed bulk RNA-seq, CD4+ T-cell parameters (including T-cell receptor data), flow cytometry data, and clinical metadata (including age and gender). The modeling included testing single-view and multi-view joint dimensionality reductions. Multi-view joint dimensionality reduction outperformed single-view methods in terms of the area under the curve and balanced accuracy, confirming the increase in predictive power to be gained. The interpretation of these findings showed that age, gender, inflammation-related gene sets, and pre-existing vaccine-specific T-cells could be associated with vaccination responsiveness. This multi-view dimensionality reduction approach complements clinical seroconversion and all single modalities. Importantly, this modeling could identify what features could predict HBV vaccine response. This methodology could be extended to other vaccination trials to identify the key features regulating responsiveness. Full article
(This article belongs to the Special Issue Immunoinformatic Approaches to Vaccine Design)
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