Ryan T. Fellers

4.1k total citations
58 papers, 2.7k citations indexed

About

Ryan T. Fellers is a scholar working on Spectroscopy, Molecular Biology and Computational Mechanics. According to data from OpenAlex, Ryan T. Fellers has authored 58 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Spectroscopy, 36 papers in Molecular Biology and 8 papers in Computational Mechanics. Recurrent topics in Ryan T. Fellers's work include Mass Spectrometry Techniques and Applications (43 papers), Advanced Proteomics Techniques and Applications (38 papers) and Metabolomics and Mass Spectrometry Studies (15 papers). Ryan T. Fellers is often cited by papers focused on Mass Spectrometry Techniques and Applications (43 papers), Advanced Proteomics Techniques and Applications (38 papers) and Metabolomics and Mass Spectrometry Studies (15 papers). Ryan T. Fellers collaborates with scholars based in United States, Germany and Canada. Ryan T. Fellers's co-authors include Neil L. Kelleher, Paul M. Thomas, Bryan P. Early, Richard D. LeDuc, Joseph B. Greer, Kenneth R. Durbin, Luca Fornelli, Philip D. Compton, Jennifer S. Brodbelt and Jared Shaw and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Ryan T. Fellers

56 papers receiving 2.7k citations

Peers

Ryan T. Fellers

SPECT

Vlad Zabrouskov United States

Philip D. Compton United States

Melanie Schroeder United States

Bryan P. Early United States

Alan M. Sandercock United Kingdom

Kenneth R. Durbin United States

Jeremy L. Norris United States

Luca Fornelli United States

Ashok Dongre United States

Graeme C. McAlister United States

Vlad Zabrouskov United States

Ryan T. Fellers

2.0k ×1.0

SPECT

1.8k ×1.1

146 ×0.7

148 ×0.7

96 ×0.6

Citations per year, relative to Ryan T. Fellers Ryan T. Fellers (= 1×) peers Vlad Zabrouskov

Countries citing papers authored by Ryan T. Fellers

Since Specialization

Citations

This map shows the geographic impact of Ryan T. Fellers'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 Ryan T. Fellers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan T. Fellers more than expected).

Fields of papers citing papers by Ryan T. Fellers

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan T. Fellers. 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 Ryan T. Fellers. The network helps show where Ryan T. Fellers may publish in the future.

Co-authorship network of co-authors of Ryan T. Fellers

This figure shows the co-authorship network connecting the top 25 collaborators of Ryan T. Fellers. A scholar is included among the top collaborators of Ryan T. Fellers 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 Ryan T. Fellers. Ryan T. Fellers is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Fellers, Ryan T., Shannon A. Raab, Kenneth R. Durbin, et al.. (2025). A Robust and Automated Platform for Charge Detection Mass Spectrometry of Megadalton Biotherapeutics. Analytical Chemistry. 97(8). 4549–4555. 1 indexed citations

Fellers, Ryan T., et al.. (2025). Proteoform-predictor: Increasing the Phylogenetic Reach of Top-Down Proteomics. Journal of Proteome Research. 24(4). 1861–1870. 1 indexed citations

Su, Pei, John P. McGee, Michael A. R. Hollas, et al.. (2025). Standardized workflow for multiplexed charge detection mass spectrometry on orbitrap analyzers. Nature Protocols. 20(6). 1485–1508. 4 indexed citations

Soye, Benjamin J. Des, John P. McGee, Michael A. R. Hollas, et al.. (2024). Automated Immunoprecipitation, Sample Preparation, and Individual Ion Mass Spectrometry Platform for Proteoforms. Analytical Chemistry. 3 indexed citations

Fellers, Ryan T., Dan Lü, Bryon Drown, et al.. (2024). MSModDetector: a tool for detecting mass shifts and post-translational modifications in individual ion mass spectrometry data. Bioinformatics. 40(6). 2 indexed citations

Su, Pei, Michael A. R. Hollas, Fatma Ayaloglu Butun, et al.. (2024). Single Cell Analysis of Proteoforms. Journal of Proteome Research. 23(6). 1883–1893. 12 indexed citations

McGee, John P., Pei Su, Kenneth R. Durbin, et al.. (2023). Automated imaging and identification of proteoforms directly from ovarian cancer tissue. Nature Communications. 14(1). 6478–6478. 17 indexed citations

Durbin, Kenneth R., Matthew T. Robey, Lilien N. Voong, et al.. (2023). ProSight Native: Defining Protein Complex Composition from Native Top-Down Mass Spectrometry Data. Journal of Proteome Research. 22(8). 2660–2668. 22 indexed citations

Yang, Manxi, Hang Hu, Pei Su, et al.. (2022). Proteoform‐Selective Imaging of Tissues Using Mass Spectrometry**. Angewandte Chemie. 134(29). 3 indexed citations

10.

Su, Pei, John P. McGee, Kenneth R. Durbin, et al.. (2022). Highly multiplexed, label-free proteoform imaging of tissues by individual ion mass spectrometry. Science Advances. 8(32). eabp9929–eabp9929. 44 indexed citations

11.

Kafader, Jared O., Rafael D. Melani, Kenneth R. Durbin, et al.. (2020). Multiplexed mass spectrometry of individual ions improves measurement of proteoforms and their complexes. Nature Methods. 17(4). 391–394. 140 indexed citations

12.

Schaffer, Leah V., Robert J. Millikin, Rachel Miller, et al.. (2019). Identification and Quantification of Proteoforms by Mass Spectrometry. PMC.

13.

Ntai, Ioanna, Luca Fornelli, Caroline J. DeHart, et al.. (2018). Precise characterization of KRAS4b proteoforms in human colorectal cells and tumors reveals mutation/modification cross-talk. Proceedings of the National Academy of Sciences. 115(16). 4140–4145. 77 indexed citations

14.

Toby, Timothy K., Michaël Abécassis, Paul M. Thomas, et al.. (2017). Proteoforms in Peripheral Blood Mononuclear Cells as Novel Rejection Biomarkers in Liver Transplant Recipients. American Journal of Transplantation. 17(9). 2458–2467. 32 indexed citations

15.

Wildburger, Norelle C., Thomas J. Esparza, Richard D. LeDuc, et al.. (2017). Diversity of Amyloid-beta Proteoforms in the Alzheimer’s Disease Brain. Scientific Reports. 7(1). 9520–9520. 118 indexed citations

16.

Fornelli, Luca, Kenneth R. Durbin, Ryan T. Fellers, et al.. (2016). Advancing Top-down Analysis of the Human Proteome Using a Benchtop Quadrupole-Orbitrap Mass Spectrometer. Journal of Proteome Research. 16(2). 609–618. 73 indexed citations

17.

Zheng, Yupeng, Luca Fornelli, Philip D. Compton, et al.. (2015). Unabridged Analysis of Human Histone H3 by Differential Top-Down Mass Spectrometry Reveals Hypermethylated Proteoforms from MMSET/NSD2 Overexpression. Molecular & Cellular Proteomics. 15(3). 776–790. 58 indexed citations

18.

Savaryn, John P., Owen S. Skinner, Luca Fornelli, et al.. (2015). Targeted analysis of recombinant NF kappa B (RelA/p65) by denaturing and native top down mass spectrometry. Journal of Proteomics. 134. 76–84. 8 indexed citations

19.

Ntai, Ioanna, Richard D. LeDuc, Ryan T. Fellers, et al.. (2015). Integrated Bottom-Up and Top-Down Proteomics of Patient-Derived Breast Tumor Xenografts. Molecular & Cellular Proteomics. 15(1). 45–56. 62 indexed citations

20.

Catherman, Adam D., Kenneth R. Durbin, Dorothy R. Ahlf, et al.. (2013). Large-scale Top-down Proteomics of the Human Proteome: Membrane Proteins, Mitochondria, and Senescence. Molecular & Cellular Proteomics. 12(12). 3465–3473. 130 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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