tailieunhanh - A gene expression database for the molecular pharmacology of cancer

Our technique determines per-application resource quo- tas in the database and storage caches, on the fly, in a transparent manner, with minimal changes to the DBMS, and no changes to existing interfaces between compo- nents. Towards this objective, we use an online perfor- mance estimation algorithm to dynamically determine the mapping between any given resource configuration setting and the corresponding application latency. While designing and implementing a performance model for guiding the resource partitioning search is non-trivial, our key insight is to design a model with sufficient ex- pressiveness to incorporate i) tracking of dynamic access patterns, and ii) sufficiently generic assumptions about the inner mechanisms of the system components and the system as. | article 2000 Nature America Inc. http 2000 Nature America Inc. http A gene expression database for the molecular pharmacology of cancer Uwe Scherf1 8 Douglas T. Ross2 Mark Waltham1 Lawrence H. Smith1 Jae K. Lee1 Lorraine Tanabe1 Kurt W. Kohn1 William C. Reinhold1 Timothy G. Myers4 Darren T. Andrews1 Dominic A. Scudiero5 Michael B. Eisen3 Edward A. Sausville6 Yves Pommier1 David Botstein3 Patrick O. Brown2 7 John N. Weinstein1 We used cDNA microarrays to assess gene expression profiles in 60 human cancer cell lines 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 patterns 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 integrate large databases on gene expression and molecular pharmacology. Introduction Gene expression profiles can be assessed for human tumours but from the pharmacological perspective there is a problem the associated treatment histories if any are generally complex fragmentary and difficult to interpret. Here we describe studies using cDNA microarrays to assess gene expression profiles in a set of 60 human cancer cell NCI60 lines that in contrast to clinical tumours have been characterized pharmacologically by treatment with more than 70 000 different agents one at a time and independently. These cells are used by the Developmental Therapeutics Program DTP of the National Cancer Institute NCI to screen potential anticancer drugs1-6. Screening the compounds for activity also profiles the cells for

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