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자료유형
학술대회자료
저자정보
Scherf, Uwe (Laboratory of Molecular Pharmacology, Division of Basic Science National Cancer Institute[NCI], National Institutes of Health[NIH]/Gene Logic Inc.) Ross, Douglas-T. (Department of Biochemistry, Stanford University School of Medicine) Waltham, Mark (Laboratory of Molecular Pharmacology, Division of Basic Science National Cancer Institute[NCI], National Institutes of Health[NIH]) Smith, Lawrence-H. (Laboratory of Molecular Pharmacology, Division of Basic Science National Cancer Institute[NCI], National Institutes of Health[NIH]) Lee, Jae-K. (Laboratory of Molecular Pharmacology, Division of Basic Science National Cancer Institute[NCI], National Institutes of Health[NIH]) Tanbe, Lorraine (Laboratory of Molecular Pharmacology, Division of Basic Science National Cancer Institute[NCI], National Institutes of Health[NIH]) Kohn, Kurt-W. (Laboratory of Molecular Pharmacology, Division of Basic Science National Cancer Institute[NCI], National Institutes of Health[NIH]) Reinhold, William-C. (Laboratory of Molecular Pharmacology, Division of Basic Science National Cancer Institute[NCI], National Institutes o) Mayers, Timothy-G. Andrews, Darren-T. Scudiero, Dominic-A. Eisen, Michael-B. Sausville, Edward-A. Pommier, Yves Botstein, David Brown, Patrick-O. Weinstein, John-N.
저널정보
한국생물정보시스템생물학회 한국생물정보시스템생물학회 심포지엄 한국생물정보시스템생물학회 2001년도 제2회 생물정보학 국제심포지엄
발행연도
2001.1
수록면
129 - 137 (9page)

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We used cDNA microarrays to assess gene expression profiles in 60 human cancer used in a drug discovery screen by the National Cancer Institute. Using these data, we linked bioinformatics and chemoinformatics by correlating gene expression and drug activity pattens in the NCI60 lines. Clustering the cell lines on the basis of gene expression yielded relationships very different from those obtained by clustering the cell lines on the basis of their response to drugs. Gene-drug relationships for the clinical agents 5-fluorouracil and L-asparaginase exemplify how variations in the transcript levels of particular genes relate to mechanisms of drug sensitivity and resistance. This is the first study to intergrate large databases on gene expression and molecular pharmacology.

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