title: MaxQuant for in-depth analysis of large SILAC datasets.
abstract: 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.
authors: Department for Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152, Martinsried, Germany.
authors: Stefka
authors: S
authors: Tyanova
authors: Matthias
authors: M
authors: Mann
authors: Jürgen
authors: J
authors: Cox
mesh_terms: D000596:Amino Acids / Q000737:chemistry*; D002478:Cells, Cultured; D002853:Chromatography, Liquid; D019295:Computational Biology / Q000379:methods*; D007553:Isotope Labeling / Q000379:methods*; D013058:Mass Spectrometry; D040901:Proteomics / Q000379:methods*; D012984:Software; D013223:Statistics as Topic / Q000379:methods*; D014584:User-Computer Interface
chemical_list: D000596:Amino Acids