%0 Journal Article
%T Classification of dendritic cell phenotypes from gene expression data
%A Giacomo Tuana
%A Viola Volpato
%A Paola Ricciardi-Castagnoli
%A Francesca Zolezzi
%A Fabio Stella
%A Maria Foti
%J BMC Immunology
%D 2011
%I BioMed Central
%R 10.1186/1471-2172-12-50
%X A data mining protocol was applied to microarray data for murine cell lines treated with various inflammatory stimuli. The learning and validation data sets consisted of 155 and 49 samples, respectively. The data mining protocol reduced the number of probe sets from 5,802 to 10, then from 10 to 6 and finally from 6 to 3. The performances of a set of supervised classification models were compared. The best accuracy, when using the six following genes --Il12b, Cd40, Socs3, Irgm1, Plin2 and Lgals3bp-- was obtained by Tree Augmented Na£żve Bayes and Nearest Neighbour (91.8%). Using the smallest set of three genes --Il12b, Cd40 and Socs3-- the performance remained satisfactory and the best accuracy was with Support Vector Machine (95.9%). These data mining models, using data for the genes Il12b, Cd40 and Socs3, were validated with a human data set consisting of 27 samples. Support Vector Machines (71.4%) and Nearest Neighbour (92.6%) gave the worst performances, but the remaining models correctly classified all the 27 samples.The genes selected by the data mining protocol proposed were shown to be informative for discriminating between inflammatory and steady-state phenotypes in dendritic cells. The robustness of the data mining protocol was confirmed by the accuracy for a human data set, when using only the following three genes: Il12b, Cd40 and Socs3. In summary, we analysed the longitudinal pattern of expression in dendritic cells stimulated with activating agents with the aim of identifying signatures that would predict or explain the dentritic cell response to an inflammatory agent.Genome-wide screening of expression profiles has provided a broad perspective on gene regulation in health and disease. Gene expression is controlled over a wide range through complex interplay between DNA regulatory proteins, microRNA molecules and epigenetic modifications determining transcript production [1-3]. For example, gene expression profiles in mouse dendritic cells (DCs) in resp
%U http://www.biomedcentral.com/1471-2172/12/50