Tyanova Stefka, Mann Matthias, Cox Jürgen
Department for Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152, Martinsried, Germany.
Methods Mol Biol. 2014;1188:351-64. doi: 10.1007/978-1-4939-1142-4_24.
Proteomics experiments can generate very large volumes of data, in particular in situations where within one experimental design many samples are compared to each other, possibly in combination with pre-fractionation of samples prior to LC-MS analysis. Here we provide a step-by-step protocol explaining how the current MaxQuant version can be used to analyze large SILAC-labeling datasets in an efficient way.
蛋白质组学实验会产生大量数据，特别是在这样的情况下：在一个实验设计中，许多样本相互比较，并且可能在液相色谱-质谱联用（LC-MS）分析之前对样本进行预分级分离。在此，我们提供一份详细的方案，解释如何使用当前版本的MaxQuant以高效方式分析大规模稳定同位素标记氨基酸在细胞培养中（SILAC）标记的数据集。
