Making sense of molecular signatures in the immune system.
The development of Functional Genomics technologies has opened new avenues to investigate the complexity of the immune system. Microarray technology has been particularly successful because of its relatively low cost and high genome coverage. Consequently to our ability to monitor the expression of a significant proportion of an organism genome, our understanding of the molecular dynamics behind cell differentiation and cell response has greatly improved. Molecular signatures associated to immune cells have provided important tools to investigate the molecular basis of diseases and have been often associated to diagnostic and prognostic markers. The availability of such large collection of data has stimulated the application of complex machine learning techniques in the attempt to link molecular signatures and cell physiology. Here we review the most recent developments in the analysis of molecular signatures in the immune system.
Davies
Nicholas J
NJ
School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK. f.falciani@bham.ac.at
Tadesse
Mahlet G T
MG
Vannucci
Marina
M
Kikuchi
Hugh
H
Trevino
Victor
V
Sarti
Donatella
D
Dragoni
Ilaria
I
Contestabile
Andrea
A
Zanders
Edward
E
Falciani
Francesco
F
D000818:Animals; D001327:Autoimmune Diseases / Q000276:immunology; D019295:Computational Biology; D020869:Gene Expression Profiling; D023281:Genomics; D006801:Humans; D007107:Immune System / Q000737:chemistry* / Q000276:immunology / Q000648:ultrastructure; D007249:Inflammation / Q000276:immunology; D007938:Leukemia / Q000276:immunology; D008214:Lymphocytes / Q000276:immunology / Q000378:metabolism; D025341:Principal Component Analysis; D040081:Protein Array Analysis; D013234:Stem Cells / Q000276:immunology / Q000378:metabolism; D017154:Stromal Cells / Q000276:immunology / Q000378:metabolism