High throughput discovery and characterization of tick and pathogen vaccine protective antigens using vaccinomics with intelligent Big Data analytic techniques

被引:25
作者
De La Fuentea, Jose [1 ,2 ]
Villar, Margarita [1 ]
Estrada-Pena, Agustin [3 ]
Olivas, Jose A. [4 ]
机构
[1] SaBio Inst Invest Recursos Cineget IREC CSIC UCLM, Ronda Toledo S-N, Ciudad Real 13005, Spain
[2] Oklahoma State Univ, Ctr Vet Hlth Sci, Dept Vet Pathobiol, Stillwater, OK 74078 USA
[3] Univ Zaragoza, Fac Vet, Zaragoza, Spain
[4] Technol & Informat Syst Inst UCLM, Ciudad Real, Spain
关键词
Tick; tick-borne diseases; vaccine; vaccinomics; Big Data analytics; graph theory; fuzzy deformable prototypes; PROTOTYPE THEORY; INFECTION; EXPRESSION; PROTEOMICS; GENE; TRANSCRIPTOMICS; CHALLENGES; STRATEGIES; PREDICTION; PROTEINS;
D O I
10.1080/14760584.2018.1493928
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Introduction: The incidence of tick-borne diseases (TBDs) is growing worldwide, and vaccines appear as the most effective and environmentally sound intervention for the prevention and control of TBDs.Areas covered: The vaccinomics approach combines omics technologies and bioinformatics for the characterization of tick-host-pathogen molecular interactions and the development of next-generation vaccines. The two main challenges of the vaccinomics approach are the integration and analysis of omics datasets, and the development of screening platforms for the identification of candidate protective antigens. To address these challenges we propose the application of intelligent Big Data analytic techniques for the high throughput discovery and characterization of tick and pathogen derived candidate vaccine protective antigens.Expert commentary: This innovative approach should improve the development and efficacy of vaccines for the control and prevention of TBDs.
引用
收藏
页码:569 / 576
页数:8
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