rements taken at different

rements taken at different 17-DMAG mw time points as well as data with missing values. Although the fundamental idea on which this method is based, effec tive summarization of time course data, is transferable to a variety of application domains, the best features describing the time series are context Inhibitors,Modulators,Libraries dependent and may differ depending Inhibitors,Modulators,Libraries on the application domain. FBPA sufficiently describes the time course by per forming dimension augmentation using biologically rele vant features, thus avoiding interpolation extrapolation, as such, the unit of the analysis is the time course itself, and not the expression measurements obtained at each time point. Because FBPA clusters all genes, it preserves information and renders unnecessary the notion of clus ter significance.

The use of biologically relevant features, together with the sufficient description of the time course, tends to Inhibitors,Modulators,Libraries produce clusters with focused biology. This study addressed the question, can we extract information about regulation of genes in irradiated and bystander cells from closely coordinated temporal gene expression profiles To do this we evaluated STEM and FBPA in both treatment conditions and showed our assessment of the results of both methodologies using computational measures as well as biological enrich ment. To measure cluster tightness, we used homogene ity, and to measure cluster separation and structure we used the average silhouette, both are described in detail in the Methods section. To compare agreements of the various clustering methods, we used the Rand Index.

We also curated a manual clustering using a subset of the data to compare clustering methods. We then assessed the biological implications of temporal cluster ing in both treatments and by both clustering methods, using gene ontology and pathway tools. Gene ontology analyses using the PANTHER tool showed that FBPA tended to cluster genes with related functions Inhibitors,Modulators,Libraries together and separated different biological processes into distinct clusters. This suggested that the features selected to describe the gene expression curves for FBPA analysis were more relevant to the underlying biological signal ing than the parameters used in STEM. Network analy sis using the Ingenuity Pathway Analysis tool was also applied to the clusters enriched in related biological processes to identify potential hubs regulating specific aspects of the radiation and bystander responses.

The overall picture of biological networks in irradiated ver sus bystander cells analyzed by FBPA clustering Cilengitide showed that temporal curves of gene expression after irradiation can be clearly differentiated into focused biological clus ters. In comparison, bystander gene expression sug gested that there is a general stress and inflammatory response in bystanders that can overshadow specific selleckchem sig naling networks. Some important and novel regulatory processes were suggested by the FBPA clustering approach, however, and we predicted the possible epige netic regulation of the meta

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