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Plant Phosphopeptide Identification and Label-Free Quantification by MaxQuant and Proteome Discoverer Software.
Li, Shalan; Zan, Haitao; Zhu, Zhe; Lu, Dandan; Krall, Leonard.
Affiliation
  • Li S; State Key Laboratory of Conservation and Utilization of Bio-Resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, China.
  • Zan H; State Key Laboratory of Conservation and Utilization of Bio-Resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, China.
  • Zhu Z; State Key Laboratory of Conservation and Utilization of Bio-Resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, China.
  • Lu D; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China.
  • Krall L; State Key Laboratory of Conservation and Utilization of Bio-Resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, China. len.krall@gmail.com.
Methods Mol Biol ; 2358: 179-187, 2021.
Article in En | MEDLINE | ID: mdl-34270055
ABSTRACT
Both the phosphorylation and dephosphorylation of plant proteins is involved in multiple biological processes, especially in regard to signal transduction. The identification of phosphopeptides from MS (mass spectrometry)-based methods and their subsequent quantification play an important role in plant phosphoproteomics analysis. Phosphopeptide(s) identification and label-free quantification can determine dynamic changes of phosphorylation events in plants. Both MaxQuant and Proteome Discoverer are professional software tools used to identify and quantify large-scale MS-based phosphoproteomic data. This chapter gives a detailed workflow of MaxQuant and Proteome Discoverer software to analyze large amounts of phosphoproteomic-related MS data for the identification and quantification of label-free plant phosphopeptides.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Type of study: Diagnostic_studies Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2021 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Type of study: Diagnostic_studies Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2021 Document type: Article Affiliation country: China