Abstract
We present a new method, link-test, to select prostate cancer biomarkers from SELDI mass spectrometry and microarray data sets. Biomarkers selected by link-test are supported by data sets from both mRNA and protein levels, and therefore results in improved robustness. Link-test determines the level of significance of the association between a microarray marker and a specific mass spectrum marker by constructing background mass spectra distributions estimated by all human protein sequences in the SWISS-PROT database. The data set consist of both microarray and mass spectrometry data from prostate cancer patients and healthy controls. A list of statistically justified prostate cancer biomarkers is reported by link-test. Cross-validation results show high prediction accuracy using the identified biomarker panel. We also employ a text-mining approach with OMIM database to validate the cancer biomarkers. The study with link-test represents one of the first cross-platform studies of cancer biomarkers.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 425-433 |
| Number of pages | 9 |
| Journal | Computational Biology and Chemistry |
| Volume | 30 |
| Issue number | 6 |
| DOIs | |
| State | Published - Dec 2006 |
Keywords
- Biomarker
- Mass spectrometry
- Microarray
- Prostate cancer
- Text mining
ASJC Scopus subject areas
- Structural Biology
- Biochemistry
- Organic Chemistry
- Computational Mathematics