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IT in Biology Medical Informatics: On the Challenge of Understanding the Data Ecosystem

机译:它在生物学和医学信息中:关于了解数据生态系统的挑战

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Data intensive disciplines, such as life sciences and medicine, are promoting vivid research activities in the area of data science. Modern technologies, such as high-throughput mass-spectrometry and sequencing, micro-arrays, high-resolution imaging, etc., produce enormous and continuously increasing amounts of data. Huge public databases provide access to aggregated and consolidated data on genome and protein sequences, biological pathways, diseases, anatomy atlases, and scientific literature. There has never been before more potentially available data to study biomedical systems, ranging from single cells to complete organisms. However, it is a non-trivial task to transform the vast amount of biomedical data into actionable, useful and usable information, triggering scientific progress and supporting patient management.
机译:数据密集学科,如生命科学和医学,正在促进数据科学领域的生动研究活动。现代技术,如高通量质谱和测序,微阵列,高分辨率成像等,产生巨大和不断增加的数据量。庞大的公共数据库提供对基因组和蛋白质序列,生物途径,疾病,解剖结构和科学文学的聚合和合并数据的访问。从未有过更多潜在的数据以研究生物医学系统,从单细胞范围到完全生物。然而,它是一种非琐碎的任务,可以将大量生物医学数据转化为可操作,有用和可用的信息,触发科学进步和支持患者管理。

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