Matthew E. Dickson

491 total citations
8 papers, 372 citations indexed

About

Matthew E. Dickson is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Matthew E. Dickson has authored 8 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Cardiology and Cardiovascular Medicine and 4 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Matthew E. Dickson's work include Renin-Angiotensin System Studies (4 papers), Hormonal Regulation and Hypertension (4 papers) and Pluripotent Stem Cells Research (2 papers). Matthew E. Dickson is often cited by papers focused on Renin-Angiotensin System Studies (4 papers), Hormonal Regulation and Hypertension (4 papers) and Pluripotent Stem Cells Research (2 papers). Matthew E. Dickson collaborates with scholars based in United States and Canada. Matthew E. Dickson's co-authors include Curt D. Sigmund, Huanyu Zhou, Rhonda Bassel‐Duby, Eric N. Olson, Min Soo Kim, M. Bridget Zimmerman, Kamal Rahmouni, Wenduo Ye, Bruce A. Posner and Zhaoning Wang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Genes & Development.

In The Last Decade

Matthew E. Dickson

8 papers receiving 366 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew E. Dickson United States 7 227 139 95 68 35 8 372
Phyllis Y. Reaves United States 10 212 0.9× 277 2.0× 81 0.9× 117 1.7× 33 0.9× 12 454
Sisi Huang China 7 218 1.0× 144 1.0× 62 0.7× 108 1.6× 19 0.5× 16 388
Jianfeng Peng United States 7 124 0.5× 195 1.4× 43 0.5× 78 1.1× 25 0.7× 9 339
Munetake Kanda Japan 8 181 0.8× 166 1.2× 45 0.5× 26 0.4× 41 1.2× 14 354
Al Muktafi Sadi Japan 10 155 0.7× 45 0.3× 110 1.2× 145 2.1× 33 0.9× 17 342
Hidenori Nishida Japan 11 205 0.9× 48 0.3× 73 0.8× 75 1.1× 22 0.6× 14 410
Xin-zheng Lu China 12 124 0.5× 109 0.8× 52 0.5× 49 0.7× 7 0.2× 31 320
Hideki Kushima Japan 11 142 0.6× 78 0.6× 170 1.8× 251 3.7× 32 0.9× 25 408
Wesley Won United States 8 104 0.5× 65 0.5× 85 0.9× 106 1.6× 31 0.9× 8 361

Countries citing papers authored by Matthew E. Dickson

Since Specialization
Citations

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

Fields of papers citing papers by Matthew E. Dickson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew E. Dickson

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew E. Dickson. A scholar is included among the top collaborators of Matthew E. 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 Matthew E. Dickson. Matthew E. Dickson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Zhou, Huanyu, María Gabriela Morales, Hisayuki Hashimoto, et al.. (2017). ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression. Genes & Development. 31(17). 1770–1783. 76 indexed citations
2.
Dickson, Matthew E., William K. Cornwell, Colby Ayers, et al.. (2016). Right atrial emptying fraction non-invasively predicts mortality in pulmonary hypertension. International journal of cardiac imaging. 32(7). 1121–1130. 18 indexed citations
3.
Zhou, Huanyu, Matthew E. Dickson, Min Soo Kim, Rhonda Bassel‐Duby, & Eric N. Olson. (2015). Akt1/protein kinase B enhances transcriptional reprogramming of fibroblasts to functional cardiomyocytes. Proceedings of the National Academy of Sciences. 112(38). 11864–11869. 136 indexed citations
4.
Grobe, Justin L., Matthew E. Dickson, Sungmi Park, et al.. (2010). Cardiovascular Consequences of Genetic Variation at −6/235 in Human Angiotensinogen Using “Humanized” Gene-Targeted Mice. Hypertension. 56(5). 981–987. 6 indexed citations
5.
Dickson, Matthew E., Xin Tian, Xuebo Liu, Deborah R. Davis, & Curt D. Sigmund. (2008). Upstream Stimulatory Factor Is Required for Human Angiotensinogen Expression and Differential Regulation by the A−20C Polymorphism. Circulation Research. 103(9). 940–947. 17 indexed citations
6.
Dickson, Matthew E., M. Bridget Zimmerman, Kamal Rahmouni, & Curt D. Sigmund. (2007). The −20 and −217 Promoter Variants Dominate Differential Angiotensinogen Haplotype Regulation in Angiotensinogen-Expressing Cells. Hypertension. 49(3). 631–639. 28 indexed citations
7.
Dickson, Matthew E. & Curt D. Sigmund. (2006). Genetic Basis of Hypertension. Hypertension. 48(1). 14–20. 89 indexed citations
8.
McAlpine, P.J., et al.. (1991). Polymorphism detected by multiple RENS in the human coagulation factor II (F2) gene. Nucleic Acids Research. 19(1). 193–193. 2 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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