Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/26246
Title: Development of Immunoinformatics Tools for Vaccine Design
Researcher: Jaiswal Varun
Guide(s): Rout Chittaranjan
Keywords: Adhesin
Epitope-based Vaccine Candidate
Host Pathogen Interaction
Jenner
Universal Influenza Vaccine (UIV)
Vaccine Design
Upload Date: 30-Sep-2014
University: Jaypee University of Information Technology, Solan
Completed Date: 17/10/2013
Abstract: Though vaccines against many diseases are available but those are not effective when strain variability is very high and immune response is poor These strain specific vaccines are also responsible for preferential selection of pathogenic strains that are not included in vaccine Therefore, prediction of broad specific vaccine candidates and design of universal epitope based vaccines are anticipated to overcome the limitations of current vaccines In this work, known immunogenic and biological information, available sequence data and other associated information were used to develop novel methods which were implemented subsequently as cybertools to predict better vaccine candidates newlineSubunit vaccines based on recombinant proteins have been effective in preventing infectious diseases and are expected to meet the demands of future vaccine development Computational approach, especially reverse vaccinology RV method has enormous potential for identification of protein vaccine candidates PVCs from a proteome of a pathogenic organism The existing protective antigen prediction software and web servers have low prediction accuracy leading to limited applications in vaccine development Besides machine learning techniques, existing softwares and web servers have considered only proteins adhesion likeliness as criterion for identification of PVCs Several non adhesin functional classes of proteins involved in host pathogen interactions and pathogenesis are known to provide protection against bacterial infections Therefore, knowledge of bacterial pathogenesis has potential to identify PVCs newline
Pagination: 
URI: http://hdl.handle.net/10603/26246
Appears in Departments:Department of Bioinformatics

Files in This Item:
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01_title.pdfAttached File126.82 kBAdobe PDFView/Open
02 _certificate.pdf71.32 kBAdobe PDFView/Open
03_declaration.pdf20.95 kBAdobe PDFView/Open
04_acknowledgement.pdf135.71 kBAdobe PDFView/Open
05_contents.pdf201.71 kBAdobe PDFView/Open
06_abbreviations.pdf30.5 kBAdobe PDFView/Open
07_list of tables figures.pdf417.14 kBAdobe PDFView/Open
08_chapter 1.pdf5.67 MBAdobe PDFView/Open
09_chapter 2.pdf6.68 MBAdobe PDFView/Open
10_chapter 3.pdf7.01 MBAdobe PDFView/Open
11_conclusion.pdf189.94 kBAdobe PDFView/Open
12_references.pdf3.16 MBAdobe PDFView/Open


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