Author

M. T. Strauss

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biochemistry· 2 Cell Biology· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Research Focus:software / tool· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:contrastive learning· 1 Approach:deep learning· 1 Assay:fluorescence / live-cell microscopy· 1 Organism:human· 1

Frequent Co-Authors

A. Auer· 1 shared A. Vorobyev· 1 shared B. Nijmeijer· 1 shared E. Krismer· 1 shared F. M. Riese· 1 shared F. M. Torun· 1 shared F. Schueder· 1 shared J. B. Müller-Reif· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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1 shared paperCell Biology

A. Auer

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Author profile →

3 papers

Recent·Most cited

AlphaPeptStats: an open-source Python package for automated, scalable and industrial-strength statistical analysis of mass spectrometry-based proteomics

E. Krismer, M. T. Strauss, M. Mann

AlphaPeptStats provides a Python package for scalable statistical analysis of proteomics data, offering tools for normalization, visualization, and automated statistical tests.

bioRxiv · Mar 10, 2023 · PreprintBiochemistry

Transparent exploration of machine learning for biomarker discovery from proteomics and omics data

M. T. Strauss, F. M. Torun, S. Virreira Winter, S. Doll, F. M. Riese, A. Vorobyev, J. B. Müller-Reif, P. E. Geyer

The paper introduces OmicLearn, an open-source web-based tool for applying machine learning to biomarker discovery in proteomics and omics data without requiring programming or bioinformatics expertise.

bioRxiv · Mar 5, 2021Biochemistry

Direct visualization of single nuclear pore complex proteins using genetically-encoded probes for DNA-PAINT

T. Schlichthaerle, M. T. Strauss, F. Schueder, A. Auer, B. Nijmeijer, M. Kueblbeck, V. Jimenez Sabinina, J. V. Thevatasan, J. Ries, J. Ellenberg, R. Jungmann

This paper develops a method to directly visualize single nuclear pore complex proteins using DNA-PAINT microscopy with genetically-encoded tags, achieving ~3 nm resolution in human cells.

bioRxiv · Mar 23, 2019Cell Biology