Wooden Benjamin, Goossens Nicolas, Hoshida Yujin, Friedman Scott L
Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.
Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York; Division of Gastroenterology and Hepatology, Department of Medical Specialties, Geneva University Hospital, Geneva, Switzerland.
Gastroenterology. 2017 Jan;152(1):53-67.e3. doi: 10.1053/j.gastro.2016.09.065. Epub 2016 Oct 20.
Technologies such as genome sequencing, gene expression profiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health information have produced large amounts of data from various populations, cell types, and disorders (big data). However, these data must be integrated and analyzed if they are to produce models or concepts about physiological function or mechanisms of pathogenesis. Many of these data are available to the public, allowing researchers anywhere to search for markers of specific biological processes or therapeutic targets for specific diseases or patient types. We review recent advances in the fields of computational and systems biology and highlight opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology to complement traditional means of diagnostic and therapeutic discovery.
诸如基因组测序、基因表达谱分析、蛋白质组学和代谢组学分析、电子病历以及患者报告的健康信息等技术,已经从不同人群、细胞类型和疾病中产生了大量数据(大数据)。然而,如果要利用这些数据生成有关生理功能或发病机制的模型或概念,就必须对其进行整合和分析。这些数据中的许多都是公开可用的,这使得世界各地的研究人员能够搜索特定生物过程的标志物,或特定疾病或患者类型的治疗靶点。我们回顾了计算生物学和系统生物学领域的最新进展,并强调了研究人员利用胃肠病学和肝病学领域的大数据集来补充传统诊断和治疗发现手段的机会。