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

Published online by Cambridge University Press:  21 September 2005

C. HEDELER ,
N. W. PATON ,
J. M. BEHNKE ,
J. E. BRADLEY ,
M. G. HAMSHERE  and
K. J. ELSE
C. HEDELER
Affiliation:
School of Computer Science, The University of Manchester, Oxford Road, Manchester M13 9PL, UK Faculty of Life Sciences, Michael Smith Building, The University of Manchester, Oxford Road, Manchester M13 9PT, UK
N. W. PATON
Affiliation:
School of Computer Science, The University of Manchester, Oxford Road, Manchester M13 9PL, UK
J. M. BEHNKE
Affiliation:
School of Biology, Nottingham University, Nottingham NG7 2RD, UK
J. E. BRADLEY
Affiliation:
School of Biology, Nottingham University, Nottingham NG7 2RD, UK
M. G. HAMSHERE
Affiliation:
School of Biology, Nottingham University, Nottingham NG7 2RD, UK
K. J. ELSE
Affiliation:
Faculty of Life Sciences, Michael Smith Building, The University of Manchester, Oxford Road, Manchester M13 9PT, UK
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Abstract

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.

Keywords

classificationsystematic immunological bioinformaticsintestinal nematode
Type
Review Article
Information
Parasitology , Volume 132 , Issue 2 , February 2006 , pp. 157 - 167
Copyright
2005 Cambridge University Press

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Supplementary material: PDF

Hedeler Supplementary data file 1

Classification of relevant information

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Supplementary material: PDF

Hedeler Supplementary data file 2

Classification of questions/tasks

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