ArticleHuman vaccines & immunotherapeutics2020
Methods for predicting vaccine immunogenicity and reactogenicity.
Article in Human vaccines & immunotherapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Development and temporal validation of a machine learning-based model to predict postoperative recurrence and guide adjuvant radiotherapy in patients with soft tissue sarcoma: a retrospective cohort study.American journal of cancer research · 2026Article
- Innovative micro physiological systems for vaccine development.Human vaccines & immunotherapeutics · 2025Review
- Advances in vaccine adjuvant development and future perspectives.Drug delivery · 2025Review
- Review
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- Overview of the Q fever vaccine development: current status and future prospects.Antonie van Leeuwenhoek · 2025Review
- Putting computational models of immunity to the test-An invited challenge to predict B.pertussis vaccination responses.PLoS computational biology · 2025Article
- VirusImmu: a novel ensemble machine learning approach for viral immunogenicity prediction.Briefings in functional genomics · 2025Article
- Immunosenescence: How Aging Increases Susceptibility to Bacterial Infections and Virulence Factors.Microorganisms · 2024Review
- How does geographical diversity shape vaccine efficacy?Clinical and experimental vaccine research · 2024Review
- Interrelated feature selection from health surveys using domain knowledge graph.Health information science and systems · 2023Article
- Q fever immunology: the quest for a safe and effective vaccine.NPJ vaccines · 2023Review
- mRNA therapeutics: New vaccination and beyond.Fundamental research · 2023Review
- Identifying Modifiable Predictors of COVID-19 Vaccine Side Effects: A Machine Learning Approach.Vaccines · 2022Article
- Signaling differences in peripheral blood mononuclear cells of high and low vaccine responders prior to, and following, vaccination in piglets.Vaccine: X · 2022Article
- Modeling COVID-19 Vaccine Adverse Effects with a Visualized Knowledge Graph Database.Healthcare (Basel, Switzerland) · 2022Article
- Evaluation of determinants of the serological response to the quadrivalent split-inactivated influenza vaccine.Molecular systems biology · 2022Article
- Use of analgesics/antipyretics in the management of symptoms associated with COVID-19 vaccination.NPJ vaccines · 2022Review
- MRI/PET multimodal imaging of the innate immune response in skeletal muscle and draining lymph node post vaccination in rats.Frontiers in immunology · 2022Article
- Machine learning in orthopaedic surgery.World journal of orthopedics · 2021Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Subjects receiving the same vaccine often show different levels of immune responses and some may even present adverse side effects to the vaccine. Systems vaccinology can combine omics data and machine learning techniques to obtain highly predictive signatures of vaccine immunogenicity and reactogenicity. Currently, several machine learning methods are already available to researchers with no background in bioinformatics. Here we described the four main steps to discover markers of vaccine immunogenicity and reactogenicity: (1) Preparing the data; (2) Selecting the vaccinees and relevant genes; (3) Choosing the algorithm; (4) Blind testing your model. With the increasing number of Systems Vaccinology datasets being generated, we expect that the accuracy and robustness of signatures of vaccine reactogenicity and immunogenicity will significantly improve.
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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 OpenQuestion graph.