Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences

被引：481

作者：

Manzoni, Claudia ^{[1
]}

Kia, Demis A. ^{[2
]}

Vandrovcova, Jana ^{[2
]}

Hardy, John ^{[2
]}

Wood, Nicholas W. ^{[3
]}

Lewis, Patrick A. ^{[4
]}

Ferrari, Raffaele ^{[2
]}

机构：

[1] Univ Reading, Reading, Berks, England

[2] UCL, London, England

[3] UCL Inst Genet, London, England

[4] Univ Reading, Cellular & Mol Neurosci, Reading, Berks, England

来源：

BRIEFINGS IN BIOINFORMATICS | 2018年 / 19卷 / 02期

基金：

英国医学研究理事会; 英国惠康基金;

关键词：

omics; bioinformatics; databases; genomics; transcriptomics; proteomics; GENE-EXPRESSION; WIDE ASSOCIATION; MISSING HERITABILITY; CONNECTIVITY MAP; ANALYSIS TOOLKIT; BIOINFORMATICS; DNA; DISCOVERY; DATABASES; RESOURCE;

D O I：

10.1093/bib/bbw114

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

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 bio-informatics 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 interdisciplinary 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.

引用

页码：286 / 302

页数：17

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