A classification of tasks for the systematic study of immune response using functional genomics data

Hedeler, C and Paton, N.W. and Behnke, Jerzy M. and Bradley, Janette E. and Hamshere, M.G. and Else, K.J. (2006) A classification of tasks for the systematic study of immune response using functional genomics data. Parasitology, 132 (2). pp. 157-167. ISSN 0031-1820

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A full understanding of the immune system and its responses to infection by different pathogens is important for the

development of anti-parasitic vaccines. A growing number of large-scale experimental techniques, such as microarrays, are being used to gain a better understanding of the immune system. To analyse the data generated by these experiments,

methods such as clustering are widely used. However, individual applications of these methods tend to analyse the

experimental data without taking publicly available biological and immunological knowledge into account systematically and in an unbiased manner. To make best use of the experimental investment, to benefit from existing evidence, and to support the findings in the experimental data, available biological information should be included in the analysis in a systematic manner. In this review we present a classification of tasks that shows how experimental data produced by studies of the immune system can be placed in a broader biological context. Taking into account available evidence, the classification can be used to identify different ways of analysing the experimental data systematically. We have used the classification to identify alternative ways of analysing microarray data, and illustrate its application using studies of immune responses in mice to infection with the intestinal nematode parasites Trichuris muris and Heligmosomoides polygyrus.

Item Type: Article
Additional Information: Copyright Cambridge University Press
Keywords: Classification, Systematic Immunological Bioinformatics, Intestinal Nematode
Schools/Departments: University of Nottingham UK Campus > Faculty of Medicine and Health Sciences > School of Life Sciences
Identification Number: https://doi.org/10.1017/S0031182005008796
Depositing User: Behnke, Professor Jerzy M.
Date Deposited: 24 Jul 2015 09:10
Last Modified: 14 Sep 2016 18:30
URI: http://eprints.nottingham.ac.uk/id/eprint/29409

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