About: Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review
Creator	Eftekhari, Samane Farajollahi, Mohammad Hemmati, Maryam Kamal Khaksaran, · Mahmodi, Zahra Mohsenzadegan, · Raoufi, Ehsan
Source	PMC
abstract	Immunoinformatics is a science that helps to create significant immunological information using bioinformatics softwares and applications. One of the most important applications of immunoinformatics is the prediction of a variety of specific epitopes for B cell recognition and T cell through MHC class I and II molecules. This method reduces costs and time compared to laboratory tests. In this state-of-the-art review, we review about 50 papers to find the latest and most used immunoinformatic tools as well as their applications for predicting the viral, bacterial and tumoral structural and linear epitopes of B and T cells. In the clinic, the main application of prediction of epitopes is for designing peptide-based vaccines. Peptide-based vaccines are a considerably potential alternative to low-cost vaccines that may reduce the risks related to the production of common vaccines.
has issue date	2019-08-20(xsd:dateTime)
bibo:doi	10.1007/s10989-019-09918-z
bibo:pmid	32435171
has license	no-cc
sha1sum (hex)	048d9f2c4e98bb9a9ddbde97b5d01aa253b24e07
schema:url	https://doi.org/10.1007/s10989-019-09918-z
resource representing a document's title	Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review
has PubMed Central identifier	PMC7224030
has PubMed identifier	32435171
schema:publication	Int J Pept Res Ther
resource representing a document's body	covid:048d9f2c4e98bb9a9ddbde97b5d01aa253b24e07#body_text
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