MaxQuant for In-Depth Analysis of Large SILAC Datasets

Tyanova, Stefka; Mann, Matthias; Cox, Jürgen

doi:10.1007/978-1-4939-1142-4_24

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MaxQuant for In-Depth Analysis of Large SILAC Datasets

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Tyanova, Stefka
Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society;

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Mann, Matthias
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Cox, Jürgen
Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society;

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引用

Tyanova, S., Mann, M., & Cox, J. (2014). MaxQuant for In-Depth Analysis of Large SILAC Datasets. In Methods in Molecular Biology; Vol. 1188 (pp. 351-364). 999 RIVERVIEW DR, STE 208, TOTOWA, NJ 07512-1165 USA: HUMANA PRESS INC.

引用: https://hdl.handle.net/11858/00-001M-0000-0024-4598-B

要旨

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.