A data review and re-assessment of ovarian cancer serum proteomic profiling.

ABSTRACT:

Background

The early detection of ovarian cancer has the potential to dramatically reduce mortality. Recently, the use of mass spectrometry to develop profiles of patient serum proteins, combined with advanced data mining algorithms has been reported as a promising method to achieve this goal. In this report, we analyze the Ovarian Dataset 8-7-02 downloaded from the Clinical Proteomics Program Databank website, using nonparametric statistics and stepwise discriminant analysis to develop rules to diagnose patients, as well as to understand general patterns in the data that may guide future research.

Results

The mass spectrometry serum profiles derived from cancer and controls exhibited numerous statistical differences. For example, use of the Wilcoxon test in comparing the in

SUBMITTER: Sorace JM 

PROVIDER: S-EPMC165662 | biostudies-literature | 2003 Jun

REPOSITORIES: biostudies-literature