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

机译:生物与医学信息学中的IT:应对理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:生命科学和医学等数据密集型学科正在促进数据科学领域的生动研究活动。高通量质谱和测序,微阵列,高分辨率成像等现代技术产生了巨大且不断增加的数据量。庞大的公共数据库可提供有关基因组和蛋白质序列,生物学途径,疾病,解剖图谱和科学文献的汇总和合并数据。从单细胞到完整的生物,从未有更多潜在的可用数据来研究生物医学系统。但是,将大量的生物医学数据转换为可操作,有用和可用的信息,从而触发科学进步并支持患者管理,是一项艰巨的任务。

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