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Preface to Biological Data Mining and its Applications in Healthcare

机译:生物数据挖掘及其在医疗保健中的应用前言

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Scientists in biology and healthcare are facing an unprecedented growth of biological and clinical data such as genetic sequences, DNA micro arrays, bimolecular interactions and pathways, bio-images, patient records, and research papers. The new-found ease of generating large amounts of biological and clinical data has made the timely analysis of the data generated an uphill task. In addition, to translate genomic research from bench to bedside, meaningful observations and discoveries will have to be drawn from a wide array of diverse data with high degrees of data heterogeneity and hierarchy, spanning from molecular biology to pharmaceutical and clinical domains.
机译:生物学和医疗保健领域的科学家正面临着前所未有的生物学和临床数据增长,例如遗传序列,DNA微阵列,双分子相互作用和途径,生物图像,患者记录和研究论文。新发现的易于生成大量生物学和临床数据的特性,使得对生成的数据进行及时分析成为一项艰巨的任务。此外,要将基因组研究从实验台转化为床头,必须从各种各样的数据中提取有意义的观察结果和发现,这些数据应具有高度的数据异质性和层次结构,范围从分子生物学到药物和临床领域。

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