Steven M. Patrie

2.4k total citations
36 papers, 1.1k citations indexed

About

Steven M. Patrie is a scholar working on Molecular Biology, Spectroscopy and Computational Mechanics. According to data from OpenAlex, Steven M. Patrie has authored 36 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 24 papers in Spectroscopy and 3 papers in Computational Mechanics. Recurrent topics in Steven M. Patrie's work include Mass Spectrometry Techniques and Applications (23 papers), Advanced Proteomics Techniques and Applications (19 papers) and Metabolomics and Mass Spectrometry Studies (10 papers). Steven M. Patrie is often cited by papers focused on Mass Spectrometry Techniques and Applications (23 papers), Advanced Proteomics Techniques and Applications (19 papers) and Metabolomics and Mass Spectrometry Studies (10 papers). Steven M. Patrie collaborates with scholars based in United States and Brazil. Steven M. Patrie's co-authors include Neil L. Kelleher, Fanyu Meng, Daniel A. Plymire, Dana Robinson, Jeffrey R. Johnson, Benjamin J. Cargile, Milan Mrksich, Shaun M. McLoughlin, Luis F. Schachner and Yi Du and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Steven M. Patrie

36 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Steven M. Patrie United States 19 730 709 91 85 60 36 1.1k
Aneika C. Leney United Kingdom 16 804 1.1× 530 0.7× 68 0.7× 44 0.5× 85 1.4× 29 1.1k
Daniel A. Polasky United States 17 934 1.3× 768 1.1× 66 0.7× 75 0.9× 69 1.1× 30 1.3k
Martin Schuerenberg Germany 5 607 0.8× 611 0.9× 50 0.5× 90 1.1× 111 1.9× 7 1.1k
Silvia A. Synowsky United Kingdom 12 613 0.8× 283 0.4× 78 0.9× 32 0.4× 48 0.8× 26 868
Kristina Lorenzen Germany 16 872 1.2× 615 0.9× 226 2.5× 68 0.8× 88 1.5× 29 1.4k
Jason M. Hogan United States 17 733 1.0× 903 1.3× 33 0.4× 76 0.9× 93 1.6× 30 1.3k
Idlir Liko United Kingdom 23 1.5k 2.0× 1.1k 1.6× 154 1.7× 96 1.1× 155 2.6× 37 2.0k
Mária Šamalíková Austria 13 368 0.5× 269 0.4× 87 1.0× 54 0.6× 51 0.8× 21 620
Margaret G. McCammon United Kingdom 12 1.1k 1.5× 485 0.7× 260 2.9× 56 0.7× 63 1.1× 17 1.6k
John Hoyes United Kingdom 12 1.0k 1.4× 1.4k 2.0× 146 1.6× 142 1.7× 184 3.1× 18 1.8k

Countries citing papers authored by Steven M. Patrie

Since Specialization
Citations

This map shows the geographic impact of Steven M. Patrie's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Steven M. Patrie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven M. Patrie more than expected).

Fields of papers citing papers by Steven M. Patrie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven M. Patrie. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Steven M. Patrie. The network helps show where Steven M. Patrie may publish in the future.

Co-authorship network of co-authors of Steven M. Patrie

This figure shows the co-authorship network connecting the top 25 collaborators of Steven M. Patrie. A scholar is included among the top collaborators of Steven M. Patrie based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Steven M. Patrie. Steven M. Patrie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Xu, Tian, Benjamin J. Des Soye, John T. Wilkins, et al.. (2025). The Proteoform Landscape of Tau from the Human Brain. Journal of Proteome Research. 24(6). 2916–2925. 1 indexed citations
2.
Cline, Erika N., Kirsten L. Viola, Carlo Condello, et al.. (2023). Amyloid β Proteoforms Elucidated by Quantitative LC/MS in the 5xFAD Mouse Model of Alzheimer’s Disease. Journal of Proteome Research. 22(11). 3475–3488. 4 indexed citations
3.
Schachner, Luis F., John P. McGee, Kevin Jooß, et al.. (2021). Reassembling protein complexes after controlled disassembly by top-down mass spectrometry in native mode. International Journal of Mass Spectrometry. 465. 116591–116591. 12 indexed citations
4.
Cline, Erika N., et al.. (2021). Online μSEC 2 -nRPLC-MS for Improved Sensitivity of Intact Protein Detection of IEF-Separated Nonhuman Primate Cerebrospinal Fluid Proteins. Analytical Chemistry. 93(50). 16741–16750. 6 indexed citations
5.
Kafader, Jared O., Rafael D. Melani, Luis F. Schachner, et al.. (2020). Native vs Denatured: An in Depth Investigation of Charge State and Isotope Distributions. Journal of the American Society for Mass Spectrometry. 31(3). 574–581. 33 indexed citations
6.
Ives, Ashley N., Kenneth R. Durbin, Bryan P. Early, et al.. (2020). Using 10,000 Fragment Ions to Inform Scoring in Native Top-down Proteomics. Journal of the American Society for Mass Spectrometry. 31(7). 1398–1409. 19 indexed citations
7.
Ro, Soo Y., Luis F. Schachner, Rahul Purohit, et al.. (2019). Native top-down mass spectrometry provides insights into the copper centers of membrane-bound methane monooxygenase. Nature Communications. 10(1). 2675–2675. 82 indexed citations
8.
9.
Patrie, Steven M.. (2016). Top-Down Mass Spectrometry: Proteomics to Proteoforms. Advances in experimental medicine and biology. 919. 171–200. 25 indexed citations
10.
Clark, Lindsay, Jacob A. Zahm, Rustam Ali, et al.. (2015). Methyl labeling and TROSY NMR spectroscopy of proteins expressed in the eukaryote Pichia pastoris. Journal of Biomolecular NMR. 62(3). 239–245. 37 indexed citations
11.
Kohler, Jennifer J. & Steven M. Patrie. (2013). Mass spectrometry of glycoproteins : methods and protocols. Humana Press eBooks. 1 indexed citations
12.
Zhang, Junmei, Michael J. Roth, Audrey N. Chang, et al.. (2013). Top-Down Mass Spectrometry on Tissue Extracts and Biofluids with Isoelectric Focusing and Superficially Porous Silica Liquid Chromatography. Analytical Chemistry. 85(21). 10377–10384. 19 indexed citations
13.
Patrie, Steven M., Michael J. Roth, & Jennifer J. Kohler. (2012). Introduction to Glycosylation and Mass Spectrometry. Methods in molecular biology. 951. 1–17. 15 indexed citations
14.
Roth, Michael J., et al.. (2012). Thin-Layer Matrix Sublimation with Vapor-Sorption Induced Co-Crystallization for Sensitive and Reproducible SAMDI-TOF MS Analysis of Protein Biosensors. Journal of the American Society for Mass Spectrometry. 23(10). 1661–1669. 10 indexed citations
15.
16.
17.
Meng, Fanyu, Yi Du, Leah M. Miller, et al.. (2004). Molecular-Level Description of Proteins from Saccharomyces cerevisiae Using Quadrupole FT Hybrid Mass Spectrometry for Top Down Proteomics. Analytical Chemistry. 76(10). 2852–2858. 62 indexed citations
18.
Patrie, Steven M., Dana Robinson, Fanyu Meng, Yi Du, & Neil L. Kelleher. (2004). Strategies for automating top-down protein analysis with Q-FTICR MS. International Journal of Mass Spectrometry. 234(1-3). 175–184. 14 indexed citations
19.
Patrie, Steven M., et al.. (2003). Electron Capture Dissociation and13C,15N Depletion for Deuterium Localization in Intact Proteins after Solution-Phase Exchange. Analytical Chemistry. 75(13). 3263–3266. 29 indexed citations
20.
Meng, Fanyu, Benjamin J. Cargile, Steven M. Patrie, et al.. (2002). Processing Complex Mixtures of Intact Proteins for Direct Analysis by Mass Spectrometry. Analytical Chemistry. 74(13). 2923–2929. 150 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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