Evidence map›Paper›PMID 38089909›Full record

ReviewPeerJ2023

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

Siti Aisyah Razali, Mohd Shahir Shamsir, Nur Farahin Ishak, Chen-Fei Low, Wan-Atirah Azemin

Open access · goldAbstract readReview
In one paragraph

Review in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Current Challenges of Vaccination in Fish Health Management.Animals : an open access journal from MDPI · 2024
    Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

Siti Aisyah RazaliFaculty of Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia.
Mohd Shahir ShamsirDepartment of Biosciences, Faculty of Science, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia.
Nur Farahin IshakFaculty of Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia.
Chen-Fei LowInstitute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Wan-Atirah AzeminSchool of Biological Sciences, Universiti Sains Malaysia, Minden, Pulau Pinang, Malaysia.
Universiti Malaysia Terengganu · MYNational University of Malaysia · MYUniversiti Sains Malaysia · MYUniversity of Technology Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

Indexed as

Fish DiseasesVaccinesAnimalsComputational BiologyEpitopesEpitopesVaccinesAdjuvantAquacultureComputational biotechnologyFish diseasesImmunoinformaticsIn silico epitope-based vaccine designLinker selectionMolecular dockingMolecular dynamics simulationVaccines

Identifiers

PMID38089909
PMCPMC10712311
OpenAlexW4389487040

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.