SIMSI-Transfer: Software-Assisted Reduction of Missing Values in Phosphoproteomic and Proteomic Isobaric Labeling Data Using Tandem Mass Spectrum Clustering

Firas Hamood, Florian P. Bayer, Mathias Wilhelm, Bernhard Kuster, Matthew The

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Isobaric stable isotope labeling techniques such as tandem mass tags (TMTs) have become popular in proteomics because they enable the relative quantification of proteins with high precision from up to 18 samples in a single experiment. While missing values in peptide quantification are rare in a single TMT experiment, they rapidly increase when combining multiple TMT experiments. As the field moves toward analyzing ever higher numbers of samples, tools that reduce missing values also become more important for analyzing TMT datasets.

Original languageEnglish
Article number100238
JournalMolecular and Cellular Proteomics
Volume21
Issue number8
DOIs
StatePublished - Aug 2022

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