Platforms for biomarker analysis using high-throughput approaches in genomics, transcriptomics, proteomics, metabolomics, and bioinformatics.

IARC scientific publications Pub Date : 2011-01-01
B Alex Merrick, Robert E London, Pierre R Bushel, Sherry F Grissom, Richard S Paules
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Abstract

Global biological responses that reflect disease or exposure biology are kinetic and highly dynamic phenomena. While high-throughput DNA sequencing continues to drive genomics, the possibility of more broadly measuring changes in gene expression has been a recent development manifested by a diversity of technical platforms. Such technologies measure transcripts, proteins and small biological molecules, or metabolites, and respectively define the fields of transcriptomics, proteomics and metabolomics that can be performed at a cell-, tissue-, or organism-wide basis. Bioinformatics is the discipline that derives knowledge from the large quantity and diversity of biological, genetic, genomic and gene expression data by integrating computer science, mathematics, statistics and graphic arts. Gene, protein and metabolite expression profiles can be thought of as snapshots of the current, poorly-mapped molecular landscape. The ultimate aim of genomic platforms is to fully map this landscape to more completely describe all of the biological interactions within a living system, during disease and toxicity, and define the behaviour and relationships of all the components of a biological system. The development of databases and knowledge bases will support the integration of data from multiple domains, as well as computational modelling. This chapter will describe the technical platform methods involving DNA sequencing, mass spectrometry, nuclear magnetic resonance combined with separation systems, and bioinformatics to derive genomic and gene expression data and include the relevant bioinformatic tools for analysis. These genomic, or omics platforms should have wide application to epidemiological studies.

使用基因组学、转录组学、蛋白质组学、代谢组学和生物信息学等高通量方法进行生物标志物分析的平台。
反映疾病或暴露生物学的全局生物反应是动态的和高度动态的现象。虽然高通量DNA测序继续推动基因组学,但更广泛地测量基因表达变化的可能性是最近技术平台多样性的发展。这些技术测量转录本、蛋白质和小生物分子或代谢物,并分别定义了转录组学、蛋白质组学和代谢组学领域,这些领域可以在细胞、组织或生物体范围内进行。生物信息学是一门综合计算机科学、数学、统计学和图形艺术,从大量多样的生物、遗传、基因组和基因表达数据中获取知识的学科。基因,蛋白质和代谢物的表达谱可以被认为是当前的快照,绘制不良的分子景观。基因组平台的最终目标是全面绘制这一景观,以更完整地描述生命系统内、疾病和毒性期间的所有生物相互作用,并定义生物系统所有组成部分的行为和关系。数据库和知识库的发展将支持来自多个领域的数据集成,以及计算建模。本章将描述涉及DNA测序,质谱,核磁共振结合分离系统和生物信息学的技术平台方法,以获得基因组和基因表达数据,并包括相关的生物信息学工具进行分析。这些基因组学或组学平台应该广泛应用于流行病学研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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