Data mining of spatial-temporal expression of genes in the human endometrium during the window of implantation

Previous studies of microarrays have produced mass data that are far from fully applied. To make full use of the available mass data and to avoid redundancy and unnecessary waste, we employed bioinformatics tools GeneSifter and Ingenuity Pathway Analysis (IPA) to mine and annotate 45 microarrays related to endometrium receptivity from GEO (Gene Expression Omnibus) database. In total, 1543 gene sets were found to express differentially, of which 148 highly regulated genes were listed as potential biomarkers of the receptive endometrium. The function and pathway analysis identified the differentially expressed genes primarily involved in immune response and cell cycle. Two networks related to the cardiovascular system and cancers were generated within the genes which changed more than 10-fold. Nine genes were validated by real-time polymerase chain reaction. It was a meaningful exploration of the existing data to acquire useful and reliable information, and our results undoubtedly provided valuable clues for further studies.