Jack E. Dixon

45.0k total citations · 9 hit papers
347 papers, 35.7k citations indexed

About

Jack E. Dixon is a scholar working on Molecular Biology, Cell Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Jack E. Dixon has authored 347 papers receiving a total of 35.7k indexed citations (citations by other indexed papers that have themselves been cited), including 255 papers in Molecular Biology, 71 papers in Cell Biology and 61 papers in Cellular and Molecular Neuroscience. Recurrent topics in Jack E. Dixon's work include Protein Tyrosine Phosphatases (67 papers), Neuropeptides and Animal Physiology (46 papers) and Peptidase Inhibition and Analysis (28 papers). Jack E. Dixon is often cited by papers focused on Protein Tyrosine Phosphatases (67 papers), Neuropeptides and Animal Physiology (46 papers) and Peptidase Inhibition and Analysis (28 papers). Jack E. Dixon collaborates with scholars based in United States, United Kingdom and China. Jack E. Dixon's co-authors include Tomohiko Maehama, Carolyn A. Worby, Kun‐Liang Guan, John M. Denu, Gregory S. Taylor, James C. Clemens, Philip Andrews, Matthew J. Wishart, Zhao Bao and Sandra E. Wiley and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Jack E. Dixon

344 papers receiving 34.9k citations

Hit Papers

The Tumor Suppressor, PTE... 1995 2026 2005 2015 1998 2004 1999 2000 2012 500 1000 1.5k 2.0k 2.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jack E. Dixon 24.8k 5.1k 4.8k 4.3k 3.9k 347 35.7k
Shigeo Ohno 22.3k 0.9× 8.0k 1.6× 3.4k 0.7× 4.0k 0.9× 2.6k 0.7× 598 34.3k
Jonathan A. Cooper 22.4k 0.9× 6.3k 1.2× 3.6k 0.7× 3.4k 0.8× 3.6k 0.9× 237 32.3k
Eisuke Nishida 26.9k 1.1× 9.9k 1.9× 3.2k 0.7× 2.9k 0.7× 2.7k 0.7× 332 37.5k
Brian A. Hemmings 33.2k 1.3× 7.2k 1.4× 3.8k 0.8× 2.3k 0.5× 3.0k 0.8× 313 42.4k
Patrick H. O’Farrell 25.0k 1.0× 7.2k 1.4× 2.9k 0.6× 4.7k 1.1× 2.3k 0.6× 140 34.2k
Melanie H. Cobb 27.3k 1.1× 5.7k 1.1× 3.9k 0.8× 2.1k 0.5× 3.0k 0.8× 278 37.1k
Akihiro Iwamatsu 18.5k 0.7× 8.4k 1.6× 4.8k 1.0× 1.9k 0.4× 2.8k 0.7× 172 29.0k
John M. Chirgwin 18.4k 0.7× 2.4k 0.5× 4.1k 0.9× 4.9k 1.2× 2.4k 0.6× 122 31.4k
Hans Jörnvall 17.6k 0.7× 3.2k 0.6× 2.2k 0.5× 2.9k 0.7× 4.4k 1.1× 542 31.0k
Richard Treisman 19.1k 0.8× 4.2k 0.8× 2.8k 0.6× 3.2k 0.7× 1.8k 0.5× 116 25.1k

Countries citing papers authored by Jack E. Dixon

Since Specialization
Citations

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

Fields of papers citing papers by Jack E. Dixon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack E. Dixon. 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 Jack E. Dixon. The network helps show where Jack E. Dixon may publish in the future.

Co-authorship network of co-authors of Jack E. Dixon

This figure shows the co-authorship network connecting the top 25 collaborators of Jack E. Dixon. A scholar is included among the top collaborators of Jack E. Dixon 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 Jack E. Dixon. Jack E. Dixon 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
3.
Mayfield, Joshua E. & Jack E. Dixon. (2023). Emerging mechanisms of regulation for endoplasmic/sarcoplasmic reticulum Ca2+ stores by secretory pathway kinase FAM20C. Current Opinion in Chemical Biology. 74. 102279–102279. 1 indexed citations
4.
Yonekawa, Takahiro, Jeffrey M. Hord, David Venzke, et al.. (2020). POMK regulates dystroglycan function via LARGE1-mediated elongation of matriglycan. eLife. 9. 18 indexed citations
5.
Zhang, Hui, Qinyu Zhu, Jixin Cui, et al.. (2018). Structure and evolution of the Fam20 kinases. Nature Communications. 9(1). 1218–1218. 50 indexed citations
6.
Chen, Jinan, Jack E. Dixon, & Gerard Manning. (2017). Genomics and evolution of protein phosphatases. Science Signaling. 10(474). 197 indexed citations
7.
Wen, Jianzhong, Junyu Xiao, Meghdad Rahdar, et al.. (2014). Xylose phosphorylation functions as a molecular switch to regulate proteoglycan biosynthesis. Proceedings of the National Academy of Sciences. 111(44). 15723–15728. 88 indexed citations
8.
Worby, Carolyn A. & Jack E. Dixon. (2014). PTEN. Annual Review of Biochemistry. 83(1). 641–669. 440 indexed citations breakdown →
9.
Tagliabracci, Vincent S., J Engel, Jianzhong Wen, et al.. (2012). Secreted Kinase Phosphorylates Extracellular Proteins That Regulate Biomineralization. Science. 336(6085). 1150–1153. 371 indexed citations breakdown →
10.
Lee, Shaun W., Douglas A. Mitchell, Andrew L. Markley, et al.. (2008). Discovery of a widely distributed toxin biosynthetic gene cluster. Proceedings of the National Academy of Sciences. 105(15). 5879–5884. 169 indexed citations
11.
Kim, Youngjun, Matthew S. Gentry, Thurl E. Harris, et al.. (2007). A conserved phosphatase cascade that regulates nuclear membrane biogenesis. Proceedings of the National Academy of Sciences. 104(16). 6596–6601. 132 indexed citations
12.
Wiley, Sandra E., Anne N. Murphy, Stuart A. Ross, Peter van der Geer, & Jack E. Dixon. (2007). MitoNEET is an iron-containing outer mitochondrial membrane protein that regulates oxidative capacity. Proceedings of the National Academy of Sciences. 104(13). 5318–5323. 246 indexed citations
13.
Gentry, Matthew S., Carolyn A. Worby, & Jack E. Dixon. (2005). Insights into Lafora disease: Malin is an E3 ubiquitin ligase that ubiquitinates and promotes the degradation of laforin. Proceedings of the National Academy of Sciences. 102(24). 8501–8506. 188 indexed citations
14.
Maehama, Tomohiko, et al.. (2004). Suppression of a phosphatidylinositol 3‐kinase signal by a specific spliced variant of Drosophila PTEN. FEBS Letters. 565(1-3). 43–47. 11 indexed citations
15.
Shao, Feng, et al.. (2003). Cleavage of Arabidopsis PBS1 by a Bacterial Type III Effector. Science. 301(5637). 1230–1233. 455 indexed citations
16.
Hinnebusch, B. Joseph, et al.. (2002). Role of Yersinia Murine Toxin in Survival of Yersinia pestis in the Midgut of the Flea Vector. Science. 296(5568). 733–735. 232 indexed citations
17.
Zhang, Zhong‐Yin & Jack E. Dixon. (1994). Protein Tyrosine Phosphatases: Mechanism of Catalysis and Substrate Specificity. Advances in enzymology and related areas of molecular biology/Advances in enzymology and related subjects. 68. 1–36. 71 indexed citations
18.
Brayton, Kelly A., Junko Aimi, Hong Qiu, et al.. (1988). Cloning, Characterization, and Sequence of a Porcine cDNA Encoding a Secreted Neuronal and Endocrine Protein. DNA. 7(10). 713–719. 28 indexed citations
19.
Meisler, Miriam H., et al.. (1987). Exclusion of close linkage between the loci for cystic fibrosis and neuropeptide Y on human chromosome 7. Cytogenetic and Genome Research. 44(2-3). 175–176. 5 indexed citations
20.
Dixon, Jack E. & Terry A. Woodford. (1984). [15] Rat pituitary Nα-acetyltransferase. Methods in enzymology on CD-ROM/Methods in enzymology. 106. 170–179. 6 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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