Bradley M. Dickson

1.8k total citations
40 papers, 971 citations indexed

About

Bradley M. Dickson is a scholar working on Molecular Biology, Statistical and Nonlinear Physics and Condensed Matter Physics. According to data from OpenAlex, Bradley M. Dickson has authored 40 papers receiving a total of 971 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 5 papers in Statistical and Nonlinear Physics and 3 papers in Condensed Matter Physics. Recurrent topics in Bradley M. Dickson's work include Epigenetics and DNA Methylation (18 papers), Cancer-related gene regulation (15 papers) and Genomics and Chromatin Dynamics (13 papers). Bradley M. Dickson is often cited by papers focused on Epigenetics and DNA Methylation (18 papers), Cancer-related gene regulation (15 papers) and Genomics and Chromatin Dynamics (13 papers). Bradley M. Dickson collaborates with scholars based in United States, Canada and China. Bradley M. Dickson's co-authors include Scott B. Rothbart, Brian D. Strahl, Krzysztof Krajewski, Evan M. Cornett, C.H. Arrowsmith, Robert M. Vaughan, Dmitri Kireev, He Huang, Michelle S. Ong and Carol Beth Post and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Bradley M. Dickson

40 papers receiving 966 citations

Peers

Bradley M. Dickson

GENET

CMN

ONCOL

AMPO

Benjamin Spink United States

Ambarish Kunwar India

Philip Winter Canada

Ilyas Yildirim United States

Robert G. Smock United States

Thomas Weidemann Germany

Joseph M. Muretta United States

Sonja A. Dames Germany

David‐Paul Minde Netherlands

Neelan J. Marianayagam United States

Benjamin Spink United States

Bradley M. Dickson

526 ×0.6

57 ×0.7

GENET

53 ×0.8

CMN

90 ×1.6

ONCOL

59 ×1.4

AMPO

Citations per year, relative to Bradley M. Dickson Bradley M. Dickson (= 1×) peers Benjamin Spink

Countries citing papers authored by Bradley M. Dickson

Since Specialization

Citations

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

Fields of papers citing papers by Bradley M. Dickson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bradley M. Dickson. 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 Bradley M. Dickson. The network helps show where Bradley M. Dickson may publish in the future.

Co-authorship network of co-authors of Bradley M. Dickson

This figure shows the co-authorship network connecting the top 25 collaborators of Bradley M. Dickson. A scholar is included among the top collaborators of Bradley M. Dickson 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 Bradley M. Dickson. Bradley M. Dickson 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

Vaughan, Robert M., Bradley M. Dickson, Katie R. Martin, & Jeffrey P. MacKeigan. (2024). Molecular dynamics simulations provide insights into ULK-101 potency and selectivity toward autophagic kinases ULK1/2. Journal of Biomolecular Structure and Dynamics. 43(13). 7106–7113. 1 indexed citations

Liu, Yanqing, Joel Hrit, Stephanie Stransky, et al.. (2024). DNA hypomethylation promotes UHRF1-and SUV39H1/H2-dependent crosstalk between H3K18ub and H3K9me3 to reinforce heterochromatin states. Molecular Cell. 85(2). 394–412.e12. 9 indexed citations

Dickson, Bradley M., et al.. (2023). Streamlined quantitative analysis of histone modification abundance at nucleosome-scale resolution with siQ-ChIP version 2.0. Scientific Reports. 13(1). 7508–7508. 3 indexed citations

Thomas, Stacey L., Ting-Hai Xu, Steven Pierce, et al.. (2023). DNA strand asymmetry generated by CpG hemimethylation has opposing effects on CTCF binding. Nucleic Acids Research. 51(12). 5997–6005. 9 indexed citations

Doud, Emma H., et al.. (2023). Global lysine methylome profiling using systematically characterized affinity reagents. Scientific Reports. 13(1). 377–377. 8 indexed citations

Dickson, Bradley M., et al.. (2020). A physical basis for quantitative ChIP-sequencing. Journal of Biological Chemistry. 295(47). 15826–15837. 8 indexed citations

Dyer, Sean, Bradley M. Dickson, & Neeraj Chhabra. (2020). Utilizing Analytics to Identify Trends in Residency Program Website Visits. Cureus. 12(2). e6910–e6910. 5 indexed citations

Vaughan, Robert M., Cari A. Sagum, Rochelle L. Tiedemann, et al.. (2020). The histone and non-histone methyllysine reader activities of the UHRF1 tandem Tudor domain are dispensable for the propagation of aberrant DNA methylation patterning in cancer cells. Epigenetics & Chromatin. 13(1). 44–44. 10 indexed citations

Vaughan, Robert M., Scott B. Rothbart, & Bradley M. Dickson. (2019). The finger loop of the SRA domain in the E3 ligase UHRF1 is a regulator of ubiquitin targeting and is required for the maintenance of DNA methylation. Journal of Biological Chemistry. 294(43). 15724–15732. 16 indexed citations

10.

Shah, Rohan N., Adrian T. Grzybowski, Evan M. Cornett, et al.. (2018). Examining the Roles of H3K4 Methylation States with Systematically Characterized Antibodies. Molecular Cell. 72(1). 162–177.e7. 56 indexed citations

11.

Cornett, Evan M., Bradley M. Dickson, & Scott B. Rothbart. (2017). Analysis of Histone Antibody Specificity with Peptide Microarrays. Journal of Visualized Experiments. 14 indexed citations

12.

Harrison, Joseph S., Evan M. Cornett, Dennis Goldfarb, et al.. (2016). Hemi-methylated DNA regulates DNA methylation inheritance through allosteric activation of H3 ubiquitylation by UHRF1. eLife. 5. 98 indexed citations

13.

Dickson, Bradley M., et al.. (2016). ArrayNinja. Methods in enzymology on CD-ROM/Methods in enzymology. 574. 53–77. 12 indexed citations

14.

Liu, Ping, X. Edward Zhou, Parker W. de Waal, et al.. (2016). The structural basis of the dominant negative phenotype of the Gαi1β1γ2 G203A/A326S heterotrimer. Acta Pharmacologica Sinica. 37(9). 1259–1272. 48 indexed citations

15.

Dickson, Bradley M.. (2016). Survey of adaptive biasing potentials: comparisons and outlook. Current Opinion in Structural Biology. 43. 63–67. 6 indexed citations

16.

Cornett, Evan M., Bradley M. Dickson, Robert M. Vaughan, et al.. (2016). Substrate Specificity Profiling of Histone-Modifying Enzymes by Peptide Microarray. Methods in enzymology on CD-ROM/Methods in enzymology. 574. 31–52. 15 indexed citations

17.

Rothbart, Scott B., Bradley M. Dickson, Jesse R. Raab, et al.. (2015). An Interactive Database for the Assessment of Histone Antibody Specificity. Molecular Cell. 59(3). 502–511. 121 indexed citations

18.

Zhong, Nan, Aiping Dong, Bradley M. Dickson, et al.. (2013). The structure–activity relationships of L3MBTL3 inhibitors: flexibility of the dimer interface. MedChemComm. 4(11). 1501–1501. 17 indexed citations

19.

Rothbart, Scott B., Bradley M. Dickson, Michelle S. Ong, et al.. (2013). Multivalent histone engagement by the linked tandem Tudor and PHD domains of UHRF1 is required for the epigenetic inheritance of DNA methylation. Genes & Development. 27(11). 1288–1298. 130 indexed citations

20.

Dickson, Bradley M.. (2011). Approaching a parameter-free metadynamics. Physical Review E. 84(3). 37701–37701. 22 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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