规范化(社会学)
污渍
计算生物学
定量分析(化学)
工作流程
数据库规范化
计算机科学
生物
化学
数据挖掘
模式识别(心理学)
色谱法
人工智能
遗传学
基因
数据库
社会学
人类学
出处
期刊:Science Signaling
[American Association for the Advancement of Science]
日期:2015-04-07
卷期号:8 (371)
被引量:199
标识
DOI:10.1126/scisignal.2005966
摘要
Immunoblotting (also known as Western blotting) combined with digital image analysis can be a reliable method for analyzing the abundance of proteins and protein modifications, but not every immunoblot-analysis combination produces an accurate result. I illustrate how sample preparation, protocol implementation, detection scheme, and normalization approach profoundly affect the quantitative performance of immunoblotting. This study implemented diagnostic experiments that assess an immunoblot-analysis workflow for accuracy and precision. The results showed that ignoring such diagnostics can lead to pseudoquantitative immunoblot data that markedly overestimate or underestimate true differences in protein abundance.
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