Computational Immunology: Models and Tools
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Computational immunology refers to a field of science, which includes high-throughput bioinformatics and genomic approaches to immunology. The primary goal of this field is to transform immunological data into computational problems, solving such problems by utilizing computational and mathematical methods, and then converting the results into immunologically relevant interpretations. Computational immunology is a subfield of bioinformatics that uses similar concepts and tools, such as sequence alignment and protein structure prediction. The other fundamental tools used in this field include C...
Computational immunology refers to a field of science, which includes high-throughput bioinformatics and genomic approaches to immunology. The primary goal of this field is to transform immunological data into computational problems, solving such problems by utilizing computational and mathematical methods, and then converting the results into immunologically relevant interpretations. Computational immunology is a subfield of bioinformatics that uses similar concepts and tools, such as sequence alignment and protein structure prediction. The other fundamental tools used in this field include ClustalW, TreeView and BLAST. It also makes use of special immunoinformatics tools like Collier-de-Perles and StructuralQuery for conducting variable domain structure analysis, and V-QUEST for conducting TR and IG sequence analysis. Computational immunology uses the immunological data for identifying infectious diseases, allergies and host responses. It is also helpful in understanding the type of specificity in immunogenicity and immune network. This book provides significant information of computational immunology to help develop a good understanding of its models and tools. It is appropriate for students seeking detailed information in this area of study as well as for experts.
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