Journal of Immunology and Immunopathology
  • Year: 2019
  • Volume: 21
  • Issue: 2

Immunoinformatics: Where Immunology Meets Bioinformatics

  • Author:
  • Naveen Kumar1,, Sandeep Bhatia2, Richa Sood3, Atul Kumar Pateriya4, Yashpal Singh Malik5
  • Total Page Count: 13
  • Page Number: 55 to 67

1Scientist, Immunology Lab, ICAR-National Institute of High Security Animal Diseases, Bhopal, Madhya Pradesh, India

2Principal Scientist, Immunology Lab, ICAR-National Institute of High Security Animal Diseases, Bhopal, Madhya Pradesh, India

3Principal Scientist, Immunology Lab, ICAR-National Institute of High Security Animal Diseases, Bhopal, Madhya Pradesh, India

4Scientist, Immunology Lab, ICAR-National Institute of High Security Animal Diseases, Bhopal, Madhya Pradesh, India

5Principal Scientist, Biological Standardization, ICAR-Indian Veterinary Research Institute, Izatnagar, Uttar Pradesh, India

*Corresponding author email id: navyog.yadav84@gmail.com

Online published on 30 November, 2019.

Abstract

One of the most challenging research areas in biology is to understand the complex immune system and the computational tools have played a pivotal role in increasing the pace of research in the field of immunology. Thus, applications of computational methods and tools in unravelling the complex immune system and thereof translating the understanding in solving the immunological problems have given rise of a new field, immunoinformatics. Among the diverse areas of research, prediction of B-and T-cell epitopes is being considered one of the major and potential translational applications of immunoinformatics. It is now possible to identify and characterise an individual's MHC allotype based on the whole genome sequencing, which is an essential and a preliminary component in designing effective vaccines and therapeutics. The potential in silico epitopes prediction methods have been developed that have made epitope mapping an easy task by decreasing the list of potential epitope candidates for experimental testing. Here, we review a range of immunoinformatics tools developed and available online for public use freely, with an emphasis on B-and T-cell epitopes prediction. We also highlight the various algorithms and methods that formed the basis of important immunoinformatics tools and discuss their strengths and weakness.

Keywords

Immunology, Bioinformatics, Immunoinformatics, Machine learning, Epitopes, Vaccines and therapeutics