Author

E. Damoc

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

Biology Disciplines

Click to filter author papers

Biochemistry· 3 Cell Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 3 Assay:proteomics· 3 Research Focus:benchmarking· 2 Approach:deep learning· 2 Approach:experimental assay· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1

Frequent Co-Authors

A. Hakimi· 2 shared A. Pashkova· 2 shared J. E. Van Eyk· 2 shared T. Arrey· 2 shared T. N. Arrey· 2 shared A. Dwivedi· 1 shared A. Giannakopulos· 1 shared A. Kholomeev· 1 shared

Activity by Year

2023-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBiochemistry

A. Hakimi

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Q. Fu, M. Vegesna, N. Sundararaman, E. Damoc, T. N. Arrey, A. Pashkova, E. Mengesha, P. Debbas, S. Joung, D. Li, S. Cheng, J. Braun, D. P. B. McGovern, C. Murray, Y. Xuan, J. E. Van Eyk

This paper introduces TEAQ, a software tool that selects clinical-grade biomarker candidates from DIA-MS data by evaluating protein quantification metrics in a discovery cohort.

bioRxiv · Mar 20, 2024 · PreprintBiochemistry

Challenging the Astral mass analyzer - up to 5300 proteins per single-cell at unseen quantitative accuracy to study cellular heterogeneity.

J. A. Bubis, T. N. Arrey, E. Damoc, B. Delanghe, J. Slovakova, T. M. Sommer, H. Kagawa, P. Pichler, N. C. Rivron, K. Mechtler, M. Matzinger

This paper introduces a high-throughput single-cell proteomics workflow achieving 5300 protein groups per cell with high accuracy, enabling the study of cellular heterogeneity and lineage differentiation.

bioRxiv · Feb 1, 2024 · PreprintBiochemistry

Protein Coronas on Functionalized Nanoparticles Enable Quantitative and Precise Large-Scale Deep Plasma Proteomics

T. Huang, J. Wang, A. Stukalov, M. K. R. Donovan, S. Ferdosi, L. Williamson, S. Just, G. Castro, L. S. Cantrell, E. Elgierari, R. W. Benz, Y. Huang, K. Motamedchaboki, A. Hakimi, T. Arrey, , D. Hornburg

This paper demonstrates that nanoparticle-based proteomics workflows enable accurate and scalable deep plasma proteomics with high precision and statistical power for biomarker discovery.

bioRxiv · Aug 28, 2023 · PreprintBiochemistry

Parallelized Acquisition of Orbitrap and Astral Analyzers Enables High-Throughput Quantitative Analysis.

H. Stewart, D. Grinfeld, A. Giannakopulos, J. Petzoldt, T. Shanley, M. Garland, E. Denisov, A. Peterson, E. Damoc, M. Zeller, T. Arrey, A. Pashkova, S. Renuse, A. Hakimi, A. Kuehn, , C. Hock

The paper introduces a new hybrid mass spectrometer combining Orbitrap and Astral analyzers to enable faster and more sensitive high-resolution accurate mass MS/MS spectra acquisition for proteomics.

bioRxiv · Jun 2, 2023Cell Biology