Computational Vaccinology
Course description:
Computational vaccinology overlaps with Computational Immunology, reverse
vaccinology,
vaccinomics, and systems vaccinology, to address questions in vaccinology. It is an
interdisciplinary field, uses computational resource and algorithm to help in design
vaccine. In
this course, recent developments in computational vaccinology, highlighting work in
epitope and
antigen identification, and the discovery of delivery vectors and adjuvants, etc. are
highlighted.
These diverse activities all have the potential to significantly reduce the laboratory
resource needed
for efficient vaccine discovery. This course offers how computational analysis of
pathogenic
genomes by epitope mapping and reverse vaccinology can provide viable vaccine
targets.
Recommended Books:
1. Rappuoli, R., & Bagnoli, F. (2011). Vaccine design: Innovative approaches and
novel
strategies. Horizon Scientific Press.
2. Sakharkar, K. R., Sakharkar, M. K., & Chandra, R. (2015). Post-Genomic
Approaches in
Drug and Vaccine Development.
3. Tong, J. C., & Ranganathan, S. (2013). Computer-aided vaccine design. Elsevier.
Course Learning Outcomes:
After the course the students will be able to apply different concepts of vaccinology in
computational domain.
Assessment system:
Quizzes 10-15%
Assignments 5-10%
MSE 30-40%
ESE 40-50%
Lecture Plan:
S.NO. Lecture Topic Quizzes Assignments
1. Introduction to Computational Vaccinology
2. Design of New Vaccines in the Genomic and Postgenomic Era
3.Application of Computational Immunology to Vaccine
Design
5. Target Identification for Vaccines
6. Computational vaccinology workflow 2
7. Cancer vaccines: computational modeling approaches
8. Reverse Vaccinology & Vaccine screening
9. Epitope-driven approaches for vaccine design 3
10. DNA vaccines 3
11. Allergen Bioinformatics
12. Identification of vaccine targets in pathogens 4
13.Computational Vaccinology: Quantitative Approaches
14. Structural and Computational Biology in the Design of
Immunogenic
15. Vaccine Antigens
