| Info. | Vol.7 - No.1 (2013.03.20) |
|---|---|
| Title | Identification of cancer-specific biomarkers by usng microarray gene expression profiling |
| Authors | Jin Choul Chai1, Soojun Park2, Hyemyung Seo1, Soo Young Cho3 & Young Seek Lee1 |
| Institutions | 1Division of Molecular & Life Sciences, Hanyang University, Ansan, Gyeonggi-do 425-791, Korea 2Bio-Medical IT Convergence Research Department, ETRI, 218 Gajeong-ro, Yusoeng-gu, Daejeon 305-700, Korea 3College of Veterinary Medicine, Institute for Bioinformatics, Bio MAX Institute, Seoul National University, Korea |
| Abstract | Carcinogenesis is a complex biological process that is affected by multiple genes, some of which can be used as biomarkers for specific tumor stages or types. An effective method for predicting such tumor markers, which are important for both diagnosis and prevention, is gene expression profiling. Here, we used a classification method and survival tests to predict cancer biomarker genes from individual cancer gene expression profiles. To validate the ability of classification in our samples, an area under the curve was calculated using support vector machine classification methods for selected genes. Twenty-three of the candidate biomarkers were correlated with patient survival. To confirm classification performance in other samples, we validated our results by comparison with breast and ovarian cancer samples. We conclude that these 23 genes might be used as cancer biomarkers. |
| Keyword | Cancer biomarker, Bioinformatics, Classification, Meta-analysis, Gene expression profile |
| PDF File |
 # 2010년도 발행분 부터는 Springer 의 BioChip Journal 페이지에서 전문을 열람하실 수 있습니다.
# 학회회원 로그인 후 [ Springer BioChip Journal 열람하기 ] 버튼을 클릭하시면 새창으로 열립니다. |
