Minimizing Bias in Label-free Quantitative Proteomics Data

In a mathematically and statistically dense paper, Rudnick et al. (2014) present a thorough exploration of factors affecting normalization for quantitative proteomics analyses.1 After an extensive review of the causes of bias, the authors have created an algorithm for improved normalization of ion current-based, label-free proteomics data that is robust enough to deal with intra- Read the rest of this article

The post Minimizing Bias in Label-free Quantitative Proteomics Data appeared first on Accelerating Science.

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