Differential co-expression analysis, a new approach in systems biology, has emerged as a complementary method to traditional differential gene expression analysis. In order to understand the genetic background of diseases, it is important to reveal the interactions of genes in diseased and healthy conditions. In this study, several cancer types (gastric carcinoma, non-small cell lung carcinoma, pancreatic ductal adenocarcinoma) were examined using differential co-expression analyses and it was discussed how these results could be used for research of diagnostic and therapeutic applications in cancer. The relevant gene expression data were obtained from National Centre for Biotechnology Information (NCBI) database. In order to characterize the differentially co-expressed genes, the normalization of each data set and statistical analyses were performed. Co-expression profiles were constructed from gene clusters that differ in their expression in each type of cancer examined and genetic networks were established to indicate whether they were expressed differently in tumour and healthy individuals. Highly interacting sub-clusters of these networks were assigned as modules and these modules were investigated whether they are significant for diagnostic and therapeutic applications of cancer.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Bioengineering
موضوع مستند نشده
Genetics
موضوع مستند نشده
Systematic biology
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