Emerging Vaccine Informatics

Details

• Alternative Title:
  J Biomed Biotechnol
• Personal Author:
  He, Yongqun ; Rappuoli, Rino ; De Groot, Anne S. ; Chen, Robert T.
• Description:
  Vaccine informatics is an emerging research area that focuses on development and applications of bioinformatics methods that can be used to facilitate every aspect of the preclinical, clinical, and postlicensure vaccine enterprises. Many immunoinformatics algorithms and resources have been developed to predict T- and B-cell immune epitopes for epitope vaccine development and protective immunity analysis. Vaccine protein candidates are predictable in silico from genome sequences using reverse vaccinology. Systematic transcriptomics and proteomics gene expression analyses facilitate rational vaccine design and identification of gene responses that are correlates of protection in vivo. Mathematical simulations have been used to model host-pathogen interactions and improve vaccine production and vaccination protocols. Computational methods have also been used for development of immunization registries or immunization information systems, assessment of vaccine safety and efficacy, and immunization modeling. Computational literature mining and databases effectively process, mine, and store large amounts of vaccine literature and data. Vaccine Ontology (VO) has been initiated to integrate various vaccine data and support automated reasoning.
• Subjects:
  Algorithms Antibodies Clinical Trials As Topic Computational Biology Computer Simulation Databases, Genetic Drug Design Epitopes, B-Lymphocyte Epitopes, T-Lymphocyte Gene Expression Profiling Genome, Human Host-Pathogen Interactions Humans Models, Theoretical Proteome Review Article Vaccines

  More +
• Source:
  J Biomed Biotechnol. 2010; 2010.
• Pubmed ID:
  21772787
• Pubmed Central ID:
  PMC3134832
• Document Type:
  Journal Article
• Funding:
  R01 AI081062/AI/NIAID NIH HHS/United States ; R01AI081062/AI/NIAID NIH HHS/United States
• Volume:
  2010
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:14af25c06169bd12ad38e330afe969983b8b2d38d69ad8de97f2b292451effbdbbb6975115b29063a6ee0a0bd8e1abf892e314f9404a66f6fdd3f177c4ceb30a
• Download URL:
  https://stacks.cdc.gov/view/cdc/60919/cdc_60919_DS1.pdf
• File Type:
  [PDF - 930.92 KB ]