组学
数据科学
药物基因组学
基因组学
蛋白质组学
数据集成
还原论
信息学
系统生物学
表观遗传学
计算生物学
计算机科学
生物
生物信息学
基因组
数据挖掘
工程类
遗传学
哲学
基因表达
电气工程
DNA甲基化
认识论
基因
作者
Claudia Manzoni,Demis A. Kia,Jana Vandrovcová,John Hardy,Nicholas William Wood,Patrick Alfryn Lewis,Raffaele Ferrari
摘要
Advances in the technologies and informatics used to generate and process large biological data sets (omics data) are promoting a critical shift in the study of biomedical sciences. While genomics, transcriptomics and proteinomics, coupled with bioinformatics and biostatistics, are gaining momentum, they are still, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. As other areas of biomedical sciences, including metabolomics, epigenomics and pharmacogenomics, are moving towards the omics scale, we are witnessing the rise of inter-disciplinary data integration strategies to support a better understanding of biological systems and eventually the development of successful precision medicine. This review cuts across the boundaries between genomics, transcriptomics and proteomics, summarizing how omics data are generated, analysed and shared, and provides an overview of the current strengths and weaknesses of this global approach. This work intends to target students and researchers seeking knowledge outside of their field of expertise and fosters a leap from the reductionist to the global-integrative analytical approach in research.
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