Author

Torsten Müller

German Cancer Research CenterORCID 0000-0002-7885-6330Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Molecular Biology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 3 Approach:experimental assay· 2 Organism:human· 2 Research Focus:protein structure prediction· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:imputation· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Jeroen KrijgsveldiD· 3 shared Mathias KalxdorfiD· 2 shared Albrecht StenzingeriD· 1 shared Daniel N. KazdaliD· 1 shared Oliver StegleiD· 1 shared Rémi LonguespéeiD· 1 shared Toman BorteçeniD· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 13 mutual co-author links

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3 shared papersSystems Biology

Jeroen KrijgsveldORCID

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3 papers

Recent·Most cited

Systems BiologyNature CommunicationsPeer-reviewedDec 12, 2023

An integrated workflow for quantitative analysis of the newly synthesized proteome

Toman Borteçen, Torsten Müller, Jeroen Krijgsveld

This paper develops a workflow called QuaNPA for analyzing newly synthesized proteins, showing its application in studying the cellular response to interferon-gamma.

20 citations

humanproteomics

BioinformaticsNature CommunicationsPeer-reviewedAug 9, 2021

IceR improves proteome coverage and data completeness in global and single-cell proteomics

Mathias Kalxdorf, Torsten Müller, Oliver Stegle, Jeroen Krijgsveld

IceR improves proteome coverage and data completeness in global and single-cell proteomics by combining DDA's identification rates with DIA's low missing value rates.

54 citations

proteomicsstatistical model

Molecular BiologyMolecular Systems BiologyPeer-reviewedJan 1, 2020

Automated sample preparation with SP3 for low-input clinical proteomics

Torsten Müller, Mathias Kalxdorf, Rémi Longuespée…·Jeroen Krijgsveld

The paper introduces autoSP3, an automated proteomics workflow for low-input clinical samples, demonstrating reproducible quantification of 500-1000 proteins from 100-1000 cells and application to FFPE lung cancer samples.

297 citationstop 1%

humanproteomics