Mark D. Distefano

7.5k total citations · 1 hit paper
169 papers, 6.0k citations indexed

About

Mark D. Distefano is a scholar working on Molecular Biology, Organic Chemistry and Cell Biology. According to data from OpenAlex, Mark D. Distefano has authored 169 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 130 papers in Molecular Biology, 73 papers in Organic Chemistry and 31 papers in Cell Biology. Recurrent topics in Mark D. Distefano's work include Click Chemistry and Applications (67 papers), Chemical Synthesis and Analysis (41 papers) and Ubiquitin and proteasome pathways (27 papers). Mark D. Distefano is often cited by papers focused on Click Chemistry and Applications (67 papers), Chemical Synthesis and Analysis (41 papers) and Ubiquitin and proteasome pathways (27 papers). Mark D. Distefano collaborates with scholars based in United States, Switzerland and Canada. Mark D. Distefano's co-authors include Jonathan K. Dozier, Mohammad Rashidian, Charuta C. Palsuledesai, Kiall F. Suazo, Melissa J. Moore, Keun‐Young Park, Christopher T. Walsh, Dongfeng Qi, Dietmar Häring and Joshua D. Ochocki and has published in prestigious journals such as Nature, Chemical Reviews and Proceedings of the National Academy of Sciences.

In The Last Decade

Mark D. Distefano

168 papers receiving 5.9k citations

Hit Papers

Directed cell migration towards softer environments 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark D. Distefano United States 42 4.0k 1.9k 810 807 776 169 6.0k
Peng R. Chen China 52 6.0k 1.5× 3.3k 1.7× 600 0.7× 963 1.2× 794 1.0× 159 8.2k
Eranthie Weerapana United States 52 5.6k 1.4× 2.7k 1.4× 688 0.8× 509 0.6× 1.2k 1.6× 128 9.3k
Katsunori Tanaka Japan 41 3.7k 0.9× 2.7k 1.4× 272 0.3× 744 0.9× 373 0.5× 291 6.4k
Andrew J. Wilson United Kingdom 50 5.2k 1.3× 2.9k 1.5× 292 0.4× 420 0.5× 1.4k 1.8× 172 8.4k
Eric J. Toone United States 38 4.4k 1.1× 2.6k 1.3× 297 0.4× 591 0.7× 306 0.4× 114 6.7k
Dieter H. Klaubert United States 28 3.5k 0.9× 1.1k 0.6× 484 0.6× 372 0.5× 280 0.4× 59 5.2k
Nediljko Budiša Germany 46 5.9k 1.5× 1.8k 0.9× 266 0.3× 555 0.7× 363 0.5× 220 7.3k
Knud J. Jensen Denmark 39 3.8k 1.0× 2.2k 1.2× 246 0.3× 488 0.6× 422 0.5× 199 5.6k
Dirk T. S. Rijkers Netherlands 41 3.7k 0.9× 1.8k 0.9× 357 0.4× 403 0.5× 306 0.4× 121 5.4k
Maarten Merkx Netherlands 50 3.9k 1.0× 694 0.4× 392 0.5× 561 0.7× 640 0.8× 167 7.0k

Countries citing papers authored by Mark D. Distefano

Since Specialization
Citations

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

Fields of papers citing papers by Mark D. Distefano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark D. Distefano

This figure shows the co-authorship network connecting the top 25 collaborators of Mark D. Distefano. A scholar is included among the top collaborators of Mark D. Distefano 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 Mark D. Distefano. Mark D. Distefano 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.
Wagner, Carston R., et al.. (2025). Engineering protein prenylation: an emerging tool for selective protein modification. Biochemical Society Transactions. 53(4). 1129–1149. 1 indexed citations
2.
Kumar, Vikas, et al.. (2024). The utility of Streptococcus mutans undecaprenol kinase for the chemoenzymatic synthesis of diverse non-natural isoprenoids. Bioorganic Chemistry. 151. 107707–107707. 2 indexed citations
3.
Suazo, Kiall F., Vartika Mishra, Linda Ottoboni, et al.. (2024). Improved synthesis and application of an alkyne-functionalized isoprenoid analogue to study the prenylomes of motor neurons, astrocytes and their stem cell progenitors. Bioorganic Chemistry. 147. 107365–107365. 1 indexed citations
4.
Suazo, Kiall F., Yiao Wang, Jonas V. Schaefer, et al.. (2024). Broadening the Utility of Farnesyltransferase-Catalyzed Protein Labeling Using Norbornene–Tetrazine Click Chemistry. Bioconjugate Chemistry. 35(7). 922–933. 3 indexed citations
6.
Milosevic, Jelena, Abirami Kugadas, Xiaoxiao Lu, et al.. (2023). Prenylcysteine oxidase 1 like protein is required for neutrophil bactericidal activities. Nature Communications. 14(1). 2761–2761. 9 indexed citations
7.
Lorimer, Ellen, et al.. (2023). GTPase splice variants RAC1 and RAC1B display isoform-specific differences in localization, prenylation, and interaction with the chaperone protein SmgGDS. Journal of Biological Chemistry. 299(6). 104698–104698. 9 indexed citations
8.
Morstein, Johannes, et al.. (2022). Photoswitchable Isoprenoid Lipids Enable Optical Control of Peptide Lipidation. ACS Chemical Biology. 17(10). 2945–2953. 9 indexed citations
9.
Wang, Yiao, et al.. (2022). Engineering Biomimetic Trogocytosis with Farnesylated Chemically Self-Assembled Nanorings. Biomacromolecules. 23(12). 5018–5035. 6 indexed citations
10.
Wang, Yiao, Carston R. Wagner, & Mark D. Distefano. (2022). Manipulating Cell Fates with Protein Conjugates. Bioconjugate Chemistry. 33(10). 1771–1784. 5 indexed citations
11.
Wang, Yiao, et al.. (2020). Engineering reversible cell–cell interactions using enzymatically lipidated chemically self-assembled nanorings. Chemical Science. 12(1). 331–340. 17 indexed citations
13.
Zhang, Yi, et al.. (2019). Site-Selective Enzymatic Labeling of Designed Ankyrin Repeat Proteins Using Protein Farnesyltransferase. Methods in molecular biology. 2033. 207–219. 6 indexed citations
14.
Veglia, Gianluigi, et al.. (2018). Synthesis and NMR Characterization of the Prenylated Peptide, a-Factor. Methods in enzymology on CD-ROM/Methods in enzymology. 614. 207–238. 2 indexed citations
15.
Palsuledesai, Charuta C., Joshua D. Ochocki, Todd W. Markowski, & Mark D. Distefano. (2014). A combination of metabolic labeling and 2D-DIGE analysis in response to a farnesyltransferase inhibitor facilitates the discovery of new prenylated proteins. Molecular BioSystems. 10(5). 1094–1103. 28 indexed citations
16.
Rashidian, Mohammad, et al.. (2012). Chemoenzymatic Reversible Immobilization and Labeling of Proteins without Prior Purification. Journal of the American Chemical Society. 134(20). 8455–8467. 82 indexed citations
17.
Mullen, Daniel G., et al.. (2012). Covalent protein–oligonucleotide conjugates by copper-free click reaction. Bioorganic & Medicinal Chemistry. 20(14). 4532–4539. 39 indexed citations
18.
Ochocki, Joshua D. & Mark D. Distefano. (2012). Prenyltransferase inhibitors: treating human ailments from cancer to parasitic infections. MedChemComm. 4(3). 476–492. 58 indexed citations
19.
Duckworth, Benjamin P., et al.. (2006). Selective Labeling of Proteins by Using Protein Farnesyltransferase. ChemBioChem. 8(1). 98–105. 98 indexed citations
20.
Miller, Susan M., Melissa J. Moore, Vincent Massey, et al.. (1989). Evidence for the participation of Cys558 and Cys559 at the active site of mercuric reductase. Biochemistry. 28(3). 1194–1205. 69 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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