Jeffrey N. Agar

8.0k total citations · 2 hit papers
73 papers, 4.7k citations indexed

About

Jeffrey N. Agar is a scholar working on Molecular Biology, Spectroscopy and Neurology. According to data from OpenAlex, Jeffrey N. Agar has authored 73 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 32 papers in Spectroscopy and 14 papers in Neurology. Recurrent topics in Jeffrey N. Agar's work include Mass Spectrometry Techniques and Applications (28 papers), Advanced Proteomics Techniques and Applications (20 papers) and Metabolomics and Mass Spectrometry Studies (19 papers). Jeffrey N. Agar is often cited by papers focused on Mass Spectrometry Techniques and Applications (28 papers), Advanced Proteomics Techniques and Applications (20 papers) and Metabolomics and Mass Spectrometry Studies (19 papers). Jeffrey N. Agar collaborates with scholars based in United States, Canada and France. Jeffrey N. Agar's co-authors include Michael K. Johnson, Dennis R. Dean, Jeverson Frazzon, Heather D. Durham, Nathalie Y.R. Agar, Boi Hanh Huynh, Carsten Krebs, Valerie L. Cash, Archer D. Smith and Aimee M. Morris and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Jeffrey N. Agar

73 papers receiving 4.6k citations

Hit Papers

Wild-type and mutant SOD1 share an aberrant conformation ... 2010 2026 2015 2020 2010 2024 100 200 300 400 500

Peers

Jeffrey N. Agar
S.V. Antonyuk United Kingdom
M C Kennedy United States
Ian M. Fearnley United Kingdom
Sagar D. Khare United States
Ashutosh Tiwari United States
Robert A. Hallewell United States
Edith Butler Gralla United States
S.V. Antonyuk United Kingdom
Jeffrey N. Agar
Citations per year, relative to Jeffrey N. Agar Jeffrey N. Agar (= 1×) peers S.V. Antonyuk

Countries citing papers authored by Jeffrey N. Agar

Since Specialization
Citations

This map shows the geographic impact of Jeffrey N. Agar'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 Jeffrey N. Agar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey N. Agar more than expected).

Fields of papers citing papers by Jeffrey N. Agar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey N. Agar. 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 Jeffrey N. Agar. The network helps show where Jeffrey N. Agar may publish in the future.

Co-authorship network of co-authors of Jeffrey N. Agar

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey N. Agar. A scholar is included among the top collaborators of Jeffrey N. Agar 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 Jeffrey N. Agar. Jeffrey N. Agar 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.
Roberts, David S., Joseph A. Loo, Yury O. Tsybin, et al.. (2024). Top-down proteomics. Nature Reviews Methods Primers. 4(1). 52 indexed citations breakdown →
2.
Abdelmoula, Walid M., Sylwia A. Stopka, Elizabeth C. Randall, et al.. (2022). massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation. Bioinformatics. 38(7). 2015–2021. 23 indexed citations
3.
Parker, Jillian A., Jean K. Chung, Zhenlu Li, et al.. (2021). Raf promotes dimerization of the Ras G-domain with increased allosteric connections. Proceedings of the National Academy of Sciences. 118(10). 40 indexed citations
4.
Smith, Lloyd M., Jeffrey N. Agar, Julia Chamot‐Rooke, et al.. (2021). The Human Proteoform Project: Defining the human proteome. Science Advances. 7(46). eabk0734–eabk0734. 145 indexed citations
5.
Aluri, Krishna, Matthew Sullivan, Roman Manetsch, et al.. (2021). Cyclic Thiosulfinates as a Novel Class of Disulfide Cleavable Cross-Linkers for Rapid Hydrogel Synthesis. Bioconjugate Chemistry. 32(3). 584–594. 12 indexed citations
6.
Abdelmoula, Walid M., Elizabeth C. Randall, Tina Kapur, et al.. (2021). Peak learning of mass spectrometry imaging data using artificial neural networks. Nature Communications. 12(1). 5544–5544. 71 indexed citations
7.
Randall, Elizabeth C., Giorgia Zadra, Paolo Chetta, et al.. (2019). Molecular Characterization of Prostate Cancer with Associated Gleason Score Using Mass Spectrometry Imaging. Molecular Cancer Research. 17(5). 1155–1165. 48 indexed citations
8.
Donnelly, Daniel P., Jeffrey N. Agar, & Steven A. Lopez. (2019). Nucleophilic substitution reactions of cyclic thiosulfinates are accelerated by hyperconjugative interactions. Chemical Science. 10(21). 5568–5575. 9 indexed citations
9.
LeDuc, Richard D., Veit Schwämmle, Michael R. Shortreed, et al.. (2018). ProForma: A Standard Proteoform Notation. Journal of Proteome Research. 17(3). 1321–1325. 28 indexed citations
10.
Pavlopoulos, Spiro, Othman Benchama, Catherine M. Rawlins, et al.. (2017). Secretion, isotopic labeling and deglycosylation of N-acylethanolamine acid amidase for biophysical studies. Protein Expression and Purification. 145. 108–117. 2 indexed citations
11.
Salisbury, Joseph P., Yun‐Wei A. Hsu, Jeniffer Quijada, et al.. (2013). A rapid MALDI-TOF mass spectrometry workflow for Drosophila melanogaster differential neuropeptidomics. Molecular Brain. 6(1). 60–60. 10 indexed citations
12.
Auclair, Jared R., Mohan Somasundaran, Karin M. Green, et al.. (2012). Mass Spectrometry Tools for Analysis of Intermolecular Interactions. Methods in molecular biology. 896. 387–398. 3 indexed citations
13.
Sugino, Ken, et al.. (2011). Recent advances in single-cell MALDI mass spectrometry imaging and potential clinical impact. Expert Review of Proteomics. 8(5). 591–604. 85 indexed citations
14.
Li, Long, et al.. (2010). Memory‐efficient calculation of the isotopic mass states of a molecule. Rapid Communications in Mass Spectrometry. 24(18). 2689–2696. 8 indexed citations
15.
Bosco, Daryl A., Gerardo Morfini, Murat Karabacak, et al.. (2010). Wild-type and mutant SOD1 share an aberrant conformation and a common pathogenic pathway in ALS. Nature Neuroscience. 13(11). 1396–1403. 544 indexed citations breakdown →
16.
Molnar, Kathleen S., Murat Karabacak, Joshua L. Johnson, et al.. (2009). A Common Property of Amyotrophic Lateral Sclerosis-associated Variants. Journal of Biological Chemistry. 284(45). 30965–30973. 59 indexed citations
17.
Karabacak, Murat, Long Li, Ashutosh Tiwari, et al.. (2008). Sensitive and Specific Identification of Wild Type and Variant Proteins from 8 to 669 kDa Using Top-down Mass Spectrometry. Molecular & Cellular Proteomics. 8(4). 846–856. 71 indexed citations
18.
Taylor, David, Bernard F. Gibbs, Edor Kabashi, et al.. (2007). Tryptophan 32 Potentiates Aggregation and Cytotoxicity of a Copper/Zinc Superoxide Dismutase Mutant Associated with Familial Amyotrophic Lateral Sclerosis. Journal of Biological Chemistry. 282(22). 16329–16335. 71 indexed citations
19.
Taylor, David, Sandra Minotti, Jeffrey N. Agar, & Heather D. Durham. (2004). Overexpression of Metallothionein Protects Cultured Motor Neurons Against Oxidative Stress, but not Mutant Cu/Zn-Superoxide Dismutase Toxicity. NeuroToxicology. 25(5). 779–792. 21 indexed citations
20.
Agar, Jeffrey N., R. F. Jack, Valerie L. Cash, et al.. (2000). Modular organization and identification of a mononuclear iron-binding site within the NifU protein. JBIC Journal of Biological Inorganic Chemistry. 5(2). 167–177. 93 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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