About: Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases
Creator	Choi, Young-Ki Oh, Soo-Jin Shin, Ok
Source	Medline; PMC
abstract	Emerging infectious diseases (EIDs) pose a major threat to public health and security. Given the dynamic nature and significant impact of EIDs, the most effective way to prevent and protect against them is to develop vaccines in advance. Systems biology approaches provide an integrative way to understand the complex immune response to pathogens. They can lead to a greater understanding of EID pathogenesis and facilitate the evaluation of newly developed vaccine-induced immunity in a timely manner. In recent years, advances in high throughput technologies have enabled researchers to successfully apply systems biology methods to analyze immune responses to a variety of pathogens and vaccines. Despite recent advances, computational and biological challenges impede wider application of systems biology approaches. This review highlights recent advances in the fields of systems immunology and vaccinology, and presents ways that systems biology-based platforms can be applied to accelerate a deeper understanding of the molecular mechanisms of immunity against EIDs.
has issue date	2018-03-01(xsd:dateTime)
bibo:doi	10.3349/ymj.2018.59.2.176
bibo:pmid	29436184
has license	cc-by-nc
sha1sum (hex)	3c3a1e707eaf3efae5ae22cced7d4850ffc1f587
schema:url	https://doi.org/10.3349/ymj.2018.59.2.176
resource representing a document's title	Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases
has PubMed Central identifier	PMC5823818
has PubMed identifier	29436184
schema:publication	Yonsei Med J
resource representing a document's body	covid:3c3a1e707eaf3efae5ae22cced7d4850ffc1f587#body_text
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