Gene expression profile of ovarian cancer dataset that helps to predict potential biomarkers

Divya, V., Anitha P. Muttagi, Seema J Patel, Gurumurthy, H. and Prashantha Nagaraja

The viral pathogens such as human papillomavirus (HPV), cytomegalovirus (CMV) and Chlamydia trachomatis are a significant risk factor for developing women mucinous epithelial ovarian cancer. The clinical and morphological distinct of ovarian cancer subtypes of frequent concurrence of endometriosis results in poor prognosis. The lack of significant markers associated with diagnosis in early stage of infection. The aim of the study is conducted oligonucleotide microarray to compare image analysis and normalization algorithms to analyze host pathogen interacting genes and proteins that reside on network of disease susceptibility. The expression is calculated on the ratio of expression levels between virus-infected tissues and normal tissues are brought great expectations for finding biomarkers that would improve patient’s treatment in the early stage of infection. The intensity of gene chip is processed and normalization is carried out using R statistical software. We have identified significant clusters of highly enriched gene markers that extent in epithelial malignancies and predicted the large expression data of candidate molecular biomarkers.

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