Immunoinformatics: A Brief Review

Abstract

A large volume of data relevant to immunology research has accumulated due to sequencing of genomes of the human and other model organisms. At the same time, huge amounts of clinical and epidemiologic data are being deposited in various scientific literature and clinical records. This accumulation of the information is like a goldmine for researchers looking for mechanisms of immune function and disease pathogenesis. Thus the need to handle this rapidly growing immunological resource has given rise to the field known as immunoinformatics. Immunoinformatics, otherwise known as computational immunology, is the interface between computer science and experimental immunology. It represents the use of computational methods and resources for the understanding of immunological information. It not only helps in dealing with huge amount of data but also plays a great role in defining new hypotheses related to immune responses. This chapter reviews classical immunology, different databases, and prediction tool. Further, it briefly describes applications of immunoinformatics in reverse vaccinology, immune system modeling, and cancer diagnosis and therapy. It also explores the idea of integrating immunoinformatics with systems biology for the development of personalized medicine. All these efforts save time and cost to a great extent.

Linear B-cell epitope prediction for in silico vaccine design: a performance review of methods available via command-line interface

“…Although epitope mapping can be carried out using several experimental techniques [11], it is time consuming and expensive, especially on a genomic scale. To address this problem and tap into the evergrowing data on epitopes deposited in biological databases daily, several computational methods for predicting conformational or linear B-cell epitopes have been published over the last decades [12][13][14] (Table 1). Despite the relatively small percentage of linear B-cell epitopes, most methods developed over the past few years focus on their prediction.…”

Translationally Controlled Tumor ProteinTCTPas Peptide Vaccine againstSchistosoma japonicum: an Immunoinformatics Approach

“…Immunoinformatics approaches have enabled the ability to design vaccines avoiding the disadvantages of the conventional methods as they reduce the time and cost required and enhance the safety and efficacy of the predicted epitopes (33,(80)(81)(82)(83)(84)(85)(86). Several epitopes were predicted in this study to design a vaccine against Schistosoma japonicum using in silico prediction tools.…”

A Novel Multi-Epitope Vaccine For Cross Protection Against Hepatitis C Virus (HCV): An Immunoinformatics Approach

“…So, it can be considered as a novel vaccine for cross-protection against HCV infection. immunoinformatics that in recent years has been highly regarded is the design of epitope-based vaccines (16)(17)(18)(19)(20)(21)(22). (28).…”