@incollection{de_immunoinformatics:_2014,
	series = {Methods in {Molecular} {Biology}},
	title = {Immunoinformatics: {A} {Brief} {Review} - {Springer}},
	copyright = {©2014 Springer Science+Business Media New York},
	isbn = {978-1-4939-1114-1, 978-1-4939-1115-8},
	shorttitle = {Immunoinformatics},
	url = {http://link.springer.com/protocol/10.1007/978-1-4939-1115-8_3#page-1},
	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.},
	number = {1184},
	urldate = {2015-05-20TZ},
	publisher = {Springer New York},
	editor = {De, Rajat K. and Tomar, Namrata},
	year = {2014},
	keywords = {B cells, Immunology, Immunomics, In silico models, Personalized medicine, Reverse vaccinology, Systems biology, T cells, allergy}
}

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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.","number":"1184","urldate":"2015-05-20TZ","publisher":"Springer New York","editor":[{"propositions":[],"lastnames":["De"],"firstnames":["Rajat","K."],"suffixes":[]},{"propositions":[],"lastnames":["Tomar"],"firstnames":["Namrata"],"suffixes":[]}],"year":"2014","keywords":"B cells, Immunology, Immunomics, In silico models, Personalized medicine, Reverse vaccinology, Systems biology, T cells, allergy","bibtex":"@incollection{de_immunoinformatics:_2014,\n\tseries = {Methods in {Molecular} {Biology}},\n\ttitle = {Immunoinformatics: {A} {Brief} {Review} - {Springer}},\n\tcopyright = {©2014 Springer Science+Business Media New York},\n\tisbn = {978-1-4939-1114-1, 978-1-4939-1115-8},\n\tshorttitle = {Immunoinformatics},\n\turl = {http://link.springer.com/protocol/10.1007/978-1-4939-1115-8_3#page-1},\n\tabstract = {A large volume of data relevant to immunology research has accumulated due to sequencing of genomes of the human and other model organisms. 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