The stark difference in clinical outcome for patients with ovarian cancer diagnosed at early stages (95% survival at 5 years) versus late stages (27.6% survival at 5 years) has driven a decades-long quest for effective biomarkers that will enable earlier detection of ovarian cancer. Yet despite intense efforts, including the application of modern high throughput technologies including transcriptomics and proteomics, there has been little improvement in performance compared to the gold standard of quantifying serum CA125 immunoreactivity paired with transvaginal ultrasound. This review describes the strategies that have been used for identification of ovarian cancer biomarkers, including the recent introduction of novel bioinformatic approaches. Results obtained using high throughput-based vs. biologically rational approaches for the discovery of diagnostic early detection biomarkers are compared and analyzed for functional enrichment.