Riding the wave of innovation: immunoinformatics in fish disease control.

Adjuvant Aquaculture Computational biotechnology Fish diseases Immunoinformatics In silico epitope-based vaccine design Linker selection Molecular docking Molecular dynamics simulation Vaccines

Journal

PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425

Informations de publication

Date de publication:
2023
Historique:
received: 25 05 2023
accepted: 17 10 2023
medline: 13 12 2023
pubmed: 13 12 2023
entrez: 13 12 2023
Statut: epublish

Résumé

The spread of infectious illnesses has been a significant factor restricting aquaculture production. To maximise aquatic animal health, vaccination tactics are very successful and cost-efficient for protecting fish and aquaculture animals against many disease pathogens. However, due to the increasing number of immunological cases and their complexity, it is impossible to manage, analyse, visualise, and interpret such data without the assistance of advanced computational techniques. Hence, the use of immunoinformatics tools is crucial, as they not only facilitate the management of massive amounts of data but also greatly contribute to the creation of fresh hypotheses regarding immune responses. In recent years, advances in biotechnology and immunoinformatics have opened up new research avenues for generating novel vaccines and enhancing existing vaccinations against outbreaks of infectious illnesses, thereby reducing aquaculture losses. This review focuses on understanding

Identifiants

pubmed: 38089909
doi: 10.7717/peerj.16419
pii: 16419
pmc: PMC10712311
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e16419

Informations de copyright

©2023 Razali et al.

Déclaration de conflit d'intérêts

The authors declare there are no competing interests.

Auteurs

Siti Aisyah Razali (SA)

Faculty of Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia.
Biological Security and Sustainability Research Interest Group (BIOSES), Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia.

Mohd Shahir Shamsir (MS)

Department of Biosciences, Faculty of Science, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia.

Nur Farahin Ishak (NF)

Faculty of Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia.

Chen-Fei Low (CF)

Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.

Wan-Atirah Azemin (WA)

School of Biological Sciences, Universiti Sains Malaysia, Minden, Pulau Pinang, Malaysia.

Classifications MeSH