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.
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Tyanova, S., Mann, M., Cox, J. (2014). MaxQuant for In-Depth Analysis of Large SILAC Datasets. In: Warscheid, B. (eds) Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC). Methods in Molecular Biology, vol 1188. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1142-4_24
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DOI: https://doi.org/10.1007/978-1-4939-1142-4_24
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Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-1141-7
Online ISBN: 978-1-4939-1142-4
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