Adrian D. Hegeman

5.7k total citations · 1 hit paper
96 papers, 3.7k citations indexed

About

Adrian D. Hegeman is a scholar working on Molecular Biology, Spectroscopy and Plant Science. According to data from OpenAlex, Adrian D. Hegeman has authored 96 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Molecular Biology, 29 papers in Spectroscopy and 29 papers in Plant Science. Recurrent topics in Adrian D. Hegeman's work include Metabolomics and Mass Spectrometry Studies (20 papers), Mass Spectrometry Techniques and Applications (16 papers) and Analytical Chemistry and Chromatography (12 papers). Adrian D. Hegeman is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (20 papers), Mass Spectrometry Techniques and Applications (16 papers) and Analytical Chemistry and Chromatography (12 papers). Adrian D. Hegeman collaborates with scholars based in United States, Switzerland and United Kingdom. Adrian D. Hegeman's co-authors include Perry A. Frey, Frank J. Ruzicka, Michael R. Sussman, Jerry D. Cohen, Amy C. Harms, Edward L. Huttlin, Clark J. Nelson, Jeffrey W. Gross, George H. Reed and Wen‐Ping Chen and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Adrian D. Hegeman

93 papers receiving 3.7k citations

Hit Papers

Comprehensive Overview of Bottom-Up Proteomics Using Mass... 2024 2026 2025 2024 10 20 30 40 50
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry
    2024 56 citations Adrian D. Hegeman et al. profile →

Peers

Adrian D. Hegeman
Jean Labarre France
Hideto Miyoshi Japan
Neil J. Oldham United Kingdom
Sandro Ghisla Germany
Antoni R. Slabas United Kingdom
Edward A. Berry United States
Rajagopal Subramanyam India
Peter Macheroux Austria
Steven Gutteridge United States
John Shanklin United States
Jean Labarre France
Adrian D. Hegeman
Citations per year, relative to Adrian D. Hegeman Adrian D. Hegeman (= 1×) peers Jean Labarre

Countries citing papers authored by Adrian D. Hegeman

Since Specialization
Citations

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

Fields of papers citing papers by Adrian D. Hegeman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Adrian D. Hegeman. 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 Adrian D. Hegeman. The network helps show where Adrian D. Hegeman may publish in the future.

Co-authorship network of co-authors of Adrian D. Hegeman

This figure shows the co-authorship network connecting the top 25 collaborators of Adrian D. Hegeman. A scholar is included among the top collaborators of Adrian D. Hegeman 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 Adrian D. Hegeman. Adrian D. Hegeman 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.
Bird, Kevin A., Patrick P. Edger, Todd C. Mockler, et al.. (2025). Homoeolog expression divergence contributes to time of day changes in transcriptomic and glucosinolate responses to prolonged water limitation in Brassica napus. The Plant Journal. 121(4). e70011–e70011.
2.
Tang, Mei Kuen, Jerry D. Cohen, Adrian D. Hegeman, et al.. (2025). Reactions of [13C]-labelled tobacco smoke with DNA to generate selected adducts formed without metabolic activation. Carcinogenesis. 46(2).
3.
Carroll, Patrick J., et al.. (2024). A multifunctional role for riboflavin in the yellow nectar of Capsicum baccatum and Capsicum pubescens. New Phytologist. 243(5). 1991–2007. 4 indexed citations
4.
Xu, Yuan, et al.. (2024). Elevated Temperature Effects on Protein Turnover Dynamics in Arabidopsis thaliana Seedlings Revealed by 15N-Stable Isotope Labeling and ProteinTurnover Algorithm. International Journal of Molecular Sciences. 25(11). 5882–5882. 3 indexed citations
5.
Roy, Rahul, Anzu Minami, Emilie C. Snell‐Rood, et al.. (2022). Convergent evolution of a blood-red nectar pigment in vertebrate-pollinated flowers. Proceedings of the National Academy of Sciences. 119(5). 19 indexed citations
6.
Cohen, Jerry D., Qian Tang, & Adrian D. Hegeman. (2022). Using targeted metabolomics to elucidate the indole auxin network in plants. Methods in enzymology on CD-ROM/Methods in enzymology. 676. 239–278. 6 indexed citations
7.
Hegeman, Adrian D., et al.. (2018). Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen. Metabolomics. 14(4). 48–48. 32 indexed citations
8.
9.
Slovin, Janet P., et al.. (2017). An improved method for fast and selective separation of carotenoids by LC–MS. Journal of Chromatography B. 1067. 34–37. 8 indexed citations
10.
Ma, Yan, Yamil Simón‐Manso, Juliane Hollender, et al.. (2015). Retention projection enables accurate calculation of liquid chromatographic retention times across labs and methods. Journal of Chromatography A. 1412. 43–51. 40 indexed citations
11.
Unger, Lucia, et al.. (2014). Hypoglycin A Concentrations in Seeds of Acer Pseudoplatanus Trees Growing on Atypical Myopathy-Affected and Control Pastures. Journal of Veterinary Internal Medicine. 28(4). 1289–1293. 48 indexed citations
12.
Wang, Yaya, Nikki Cecil M. Magdaong, Volker S. Urban, et al.. (2014). Impact of esterified bacteriochlorophylls on the biogenesis of chlorosomes in Chloroflexus aurantiacus. Photosynthesis Research. 122(1). 69–86. 8 indexed citations
13.
Roe, Mikel R., Jerry D. Cohen, & Adrian D. Hegeman. (2013). Targeted Deuteration of Polyphenolics for Their Qualitative and Quantitative Metabolomic Analysis in Plant-Derived Extracts. Methods in molecular biology. 1083. 17–29. 3 indexed citations
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Yang, Xiaoyuan, Wen‐Ping Chen, Aaron Rendahl, et al.. (2010). Measuring the turnover rates of Arabidopsis proteins using deuterium oxide: an auxin signaling case study. The Plant Journal. 63(4). 680–695. 45 indexed citations
17.
Frey, Perry A., Adrian D. Hegeman, & Frank J. Ruzicka. (2008). The Radical SAM Superfamily. Critical Reviews in Biochemistry and Molecular Biology. 43(1). 63–88. 452 indexed citations
18.
Nelson, Clark J., Edward L. Huttlin, Adrian D. Hegeman, Amy C. Harms, & Michael R. Sussman. (2007). Implications of 15N‐metabolic labeling for automated peptide identification in Arabidopsis thaliana. PROTEOMICS. 7(8). 1279–1292. 85 indexed citations
19.
Allard, S.T.M., Konstantinos Beis, Marie‐France Giraud, et al.. (2002). Toward a Structural Understanding of the Dehydratase Mechanism. Structure. 10(1). 81–92. 87 indexed citations
20.
Hegeman, Adrian D., et al.. (1996). Identification of genes expressed after noise exposure in the chick basilar papilla. Hearing Research. 96(1-2). 20–32. 46 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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