Functional annotation of gene expression data To systematically annotate and predict biological pro cesses and pathways of target genes affected by the sup pression quality control of cyclin D levels we employed three strategies 1) GO term annotation and enrichment analysis using GoMiner . 2) KEGG pathways annotation using the selection of 38 human cancer and signaling specific KEGG pathways. Inhibitors,Modulators,Libraries GoMiner was used to determine whether the target genes as well as the corresponding proteins in PPI net works showed enrichment in certain GO biological pro cesses. Enrichment is defined as the proportion of changed genes in the category relative to the expected proportion for the entire microarray. Significance was tested using one sided Fishers exact test and the false discovery rate threshold Inhibitors,Modulators,Libraries was set at 0.

05, with Inhibitors,Modulators,Libraries 1000 randomizations. Additional functional annotation was performed using a selection of 38 biological signaling and disease related KEGG pathways. To assess enrichment for specific KEGG pathways representation in the target genes the proportion of target genes was compared with propor tion of genes expected from the entire gene set on U133 Plus 2. 0 microarray using Fishers exact test. Obtained p values were corrected for multiple testing of the 38 KEGG pathways. Experimental PPI networks were generated by query ing the I2D database with the target genes to obtain cor responding proteins and their immediate interacting partners.

Relationships between the interacting proteins were added to the same network, resulting in PPI networks with 576 proteins and 4557 interactions for CCND3 uniquely deregulated genes, 1362 proteins and 12135 interactions Inhibitors,Modulators,Libraries for CCND1 uniquely Inhibitors,Modulators,Libraries deregulated genes, and 289 pro teins and 1763 interactions for common genes deregu lated in both CCND1/CCND3 siRNA, used in subsequent analyses. The proteins in PPI networks were annotated with GO biological processes and tested for enrichment using GoMiner as described above. Signifi cant KEGG pathways were determined for target genes and their interacting proteins in PPI networks by testing their proportions against expected proportions estimated from 1000 randomly generated PPI networks obtained by querying a subset of I2D for genes represented on Affymetrix U133 Plus 2. 0 chip, with the same number of proteins as cyclin D1/D3 deregulated target genes matched in I2D. The Students t test was then used to compare the proportion in the experimentally determined PPI network against the dis tributions in random networks, as previously described. Obtained p values were corrected for multiple test http://www.selleckchem.com/products/BI6727-Volasertib.html ing of the 38 KEGG pathways used for annotation. PPI networks were annotated, visualized and analyzed using NAViGaTOR v2. 0.