蛋白质组学
生物标志物
生物标志物发现
定量蛋白质组学
蛋白质组
仿形(计算机编程)
计算生物学
计算机科学
数据科学
生物信息学
生物
生物化学
基因
操作系统
作者
Viviana Greco,Cristian Piras,Luisa Pieroni,Andrea Urbani
标识
DOI:10.1007/978-1-4939-7057-5_1
摘要
Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.
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