Kathrin Korff

Limited Impact of Column Chemistry and Length on Proteome Coverage Under High-Speed DIA

Alicia-Sophie Schebesta, Kathrin Korff, Ericka C.M. Itang, Vincent Albrecht et autres

The evolution of mass spectrometry (MS)-based proteomics has been driven by continuous technological advances in sample preparation, liquid-phase separations, instrumentation, and data acquisition. Chromatographic performance has been recognized as a contributing factor to identification depth, particularly on earlier-generation MS platforms. Recent advances …

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In situ polymerized monolith tips for reproducible, format-flexible proteomic sample preparation applied to biofluids

Kathrin Korff, Lukas T. Henneberg, Denys Oliinyk, Nils Eikmeier et autres

Abstract Sample preparation increasingly sets the throughput and reproducibility of mass spectrometry (MS)-based proteomics. StageTips (stop-and-go extraction tips) and variants thereof have long been common implements to purify samples, and we recently extended the concept to solid-phase extraction capture (SPEC) tips, in …

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Deeper is not always better in plasma proteomics

Huanhuan Gao, Kathrin Korff, Matthias Mann, Tiannan Guo

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Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

The circulating blood proteome comprises soluble and cellular components that reflect physiological and pathological states across tissues. Advances in mass spectrometry and affinity-based proteomics have improved sensitivity and throughput, enabling the generation of public blood proteomics resources. However, comprehensive assessments of these …

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Additional file 13 of Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

Additional file 13: Fig. S4. Overlaps and differences among resources on the proteome of each blood cell type. Comparison of proteins shared across databases for each cell type, shown as one UpSet plot per cell type.

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Additional file 12 of Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

Additional file 12: Table S3. Blood cell types of proteomes by combining resources. A table showing the number of proteins per cell type after the combination of several resources. The number of proteins only reported in one dataset and the overlap percentage …

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Additional file 13 of Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

Additional file 13: Fig. S4. Overlaps and differences among resources on the proteome of each blood cell type. Comparison of proteins shared across databases for each cell type, shown as one UpSet plot per cell type.

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Additional file 9 of Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

Additional file 9: Fig. 3S. Comparative analysis of serum proteomics databases. Comparison of serum proteome data from GPMDB and PaxDb, highlighting similarities and differences in protein representation.

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Additional file 1 of Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

Additional file 1: Table S1. Comparative overview of proteomic techniques used in blood analysis at the time of writing. This table compares key aspects of mass spectrometry and affinity proteomics techniques.

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Additional file 7 of Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

Additional file 7: Data S3. Combined Circulating proteome. Methodology and curated list of the circulating proteome generated by integrating multiple databases, with a link to the GitHub repository.

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Additional file 2 of Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

Additional file 2: Table S2. Relevant blood plasma and cell type datasets.

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Additional file 12 of Blood proteomics: insights from public data

A. Larrea, Chengxin Dai, Alejandro J. Brenes, Kathrin Korff et autres

Additional file 12: Table S3. Blood cell types of proteomes by combining resources. A table showing the number of proteins per cell type after the combination of several resources. The number of proteins only reported in one dataset and the overlap percentage …

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