assessing the biological significance of gene expression signatures and co-expression modules by studying their network properties评估基因表达的生物学意义的签名和co-expression模块通过研究他们的网络属性.pdf

Assessing the Biological Significance of Gene Expression Signatures and Co-Expression Modules by Studying Their Network Properties Pablo Minguez1¤, Joaquin Dopazo1,2,3* ´ ´ 1 Department of Bioinformatics and Genomics, Centro de Investigacion Prıncipe Felipe (CIPF), Valencia, Spain, 2 CIBER de Enfermedades Raras (CIBERER), Valencia, Spain, 3 Functional Genomics Node, (INB) at CIPF, Valencia, Spain Abstract Microarray experiments have been extensively used to define signatures, which are sets of genes that can be considered markers of experimental conditions (typically diseases). Paradoxically, in spite of the apparent functional role that might be attributed to such gene sets, signatures do not seem to be reproducible across experiments. Given the close relationship between function and protein interaction, network properties can be used to study to what extent signatures are composed of genes whose resulting proteins show a considerable level of interaction (and consequently a putative common functional role). We have analysed 618 signatures and 507 modules of co-expression in cancer looking for significant values of four main protein-protein interaction (PPI) network parameters: connection degree, cluster coefficient, betweenness and number of components. A total of 3904 gene ontology (GO) modules, 146 KEGG pathways, and 263 Biocarta pathways have been used as functional modules of reference. Co-expression modules found in microarray experiments display a high level of connectivity, similar to the one shown by conventional modules based on functional definitions (GO, KEGG and Biocarta). A general observation for all the classes studied is that the networks formed by the modu