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Volumn 3005, Issue , 2004, Pages 41-51

Analysis of proteomic pattern data for cancer detection

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DISEASES; EVOLUTIONARY ALGORITHMS; UROLOGY;

EID: 35048820555     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24653-4_5     Document Type: Article
Times cited : (17)

References (6)
  • 1
    • 0037399476 scopus 로고    scopus 로고
    • SELDI-TOF MS for diagnostic proteomics
    • H.J. Issaq et al. SELDI-TOF MS for diagnostic proteomics. Anal. Chem., 75(7):148A-155A, 2003.
    • (2003) Anal. Chem. , vol.75 , Issue.7
    • Issaq, H.J.1
  • 2
    • 0037120949 scopus 로고    scopus 로고
    • Serum proteomic patterns for detection of prostate cancer
    • Petricoin E.F. et al. Serum proteomic patterns for detection of prostate cancer. Journal of the National Cancer Institute, 94(20):1576-1578, 2002.
    • (2002) Journal of the National Cancer Institute , vol.94 , Issue.20 , pp. 1576-1578
    • Petricoin, E.F.1
  • 3
    • 0037116832 scopus 로고    scopus 로고
    • Use of proteomic patterns in serum to identify ovarian cancer
    • Petricoin E.F. et al. Use of proteomic patterns in serum to identify ovarian cancer. The Lancet, 359(9306):572-7, 2002.
    • (2002) The Lancet , vol.359 , Issue.9306 , pp. 572-577
    • Petricoin, E.F.1
  • 4
    • 0038021028 scopus 로고    scopus 로고
    • A comparative study on feature selection and classification methods using gene expression profiles and proteomic patterns
    • H. Liu, J. Li, and L. Wong. A comparative study on feature selection and classification methods using gene expression profiles and proteomic patterns. Genome Informatics, 13:51-60, 2002.
    • (2002) Genome Informatics , vol.13 , pp. 51-60
    • Liu, H.1    Li, J.2    Wong, L.3
  • 5
    • 0013161560 scopus 로고    scopus 로고
    • On feature selection: Learning with exponentially many irrelevant features as training examples
    • Morgan Kaufmann, San Francisco, CA
    • Andrew Y. Ng. On feature selection: learning with exponentially many irrelevant features as training examples. In Proc. 15th International Conf. on Machine Learning, pages 404-412. Morgan Kaufmann, San Francisco, CA, 1998.
    • (1998) Proc. 15th International Conf. on Machine Learning , pp. 404-412
    • Ng, A.Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.