组学
蛋白质组学
仿形(计算机编程)
代谢组学
表观遗传学
基因组学
数据科学
计算生物学
生物信息学
计算机科学
生物
遗传学
基因组
基因表达
操作系统
基因
DNA甲基化
作者
Signe Altmäe,Francisco J. Esteban,Anneli Stavréus-Evers,Carlos Simón,Linda C. Giudice,Bruce A. Lessey,José A. Horcajadas,Nick S. Macklon,Thomas D’Hooghe,Cristina Campoy,Bart C.J.M. Fauser,Lois A. Salamonsen,Andres Salumets
出处
期刊:Human Reproduction Update
[Oxford University Press]
日期:2013-09-29
卷期号:20 (1): 12-28
被引量:124
标识
DOI:10.1093/humupd/dmt048
摘要
BACKGROUND‘Omics’ high-throughput analyses, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, are widely applied in human endometrial studies. Analysis of endometrial transcriptome patterns in physiological and pathophysiological conditions has been to date the most commonly applied ‘omics’ technique in human endometrium. As the technologies improve, proteomics holds the next big promise for this field. The ‘omics’ technologies have undoubtedly advanced our knowledge of human endometrium in relation to fertility and different diseases. Nevertheless, the challenges arising from the vast amount of data generated and the broad variation of ‘omics’ profiling according to different environments and stimuli make it difficult to assess the validity, reproducibility and interpretation of such ‘omics’ data. With the expansion of ‘omics’ analyses in the study of the endometrium, there is a growing need to develop guidelines for the design of studies, and the analysis and interpretation of ‘omics’ data.
科研通智能强力驱动
Strongly Powered by AbleSci AI