James N. Topper

8.0k total citations · 3 hit papers
45 papers, 6.5k citations indexed

About

James N. Topper is a scholar working on Molecular Biology, Surgery and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, James N. Topper has authored 45 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 6 papers in Surgery and 6 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in James N. Topper's work include Angiogenesis and VEGF in Cancer (9 papers), TGF-β signaling in diseases (9 papers) and RNA and protein synthesis mechanisms (8 papers). James N. Topper is often cited by papers focused on Angiogenesis and VEGF in Cancer (9 papers), TGF-β signaling in diseases (9 papers) and RNA and protein synthesis mechanisms (8 papers). James N. Topper collaborates with scholars based in United States, Germany and Taiwan. James N. Topper's co-authors include Michael A. Gimbrone, Jiexing Cai, Tobi Nagel, David A. Clayton, Keith R. Anderson, D Falb, Dean Falb, Guillermo García‐Cardeña, YongYao Xu and Yubin Qiu and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

James N. Topper

45 papers receiving 6.4k citations

Hit Papers

The MAD-Related Protein Smad7 Associates with the TGFβ Re... 1996 2026 2006 2016 1997 1996 2000 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James N. Topper United States 36 4.0k 957 904 736 683 45 6.5k
Hikaru Ueno Japan 46 4.7k 1.2× 1.0k 1.1× 783 0.9× 645 0.9× 1.2k 1.7× 109 7.7k
Bruce A. Keyt United States 31 5.1k 1.3× 680 0.7× 514 0.6× 599 0.8× 950 1.4× 79 9.9k
M Chiariello Italy 43 4.5k 1.1× 869 0.9× 1.6k 1.7× 771 1.0× 907 1.3× 215 8.6k
Enrico V. Avvedimento Italy 47 3.9k 1.0× 466 0.5× 369 0.4× 989 1.3× 644 0.9× 93 7.5k
Christopher D. Kontos United States 40 3.2k 0.8× 662 0.7× 584 0.6× 538 0.7× 574 0.8× 88 5.1k
Xiaoping Du United States 50 2.3k 0.6× 841 0.9× 1.4k 1.5× 1.2k 1.7× 452 0.7× 104 7.2k
Catherine Butterfield United States 22 3.8k 1.0× 847 0.9× 546 0.6× 682 0.9× 1.4k 2.1× 33 6.5k
Anton J.G. Horrevoets Netherlands 43 4.2k 1.0× 1.0k 1.1× 1.1k 1.2× 1.3k 1.7× 373 0.5× 106 7.1k
Yutaka Nakashima Japan 38 2.0k 0.5× 1.6k 1.7× 955 1.1× 1.4k 1.9× 793 1.2× 124 6.7k
Wei Kong China 48 2.9k 0.7× 913 1.0× 1.1k 1.2× 1.1k 1.6× 607 0.9× 224 7.3k

Countries citing papers authored by James N. Topper

Since Specialization
Citations

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

Fields of papers citing papers by James N. Topper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James N. Topper. 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 James N. Topper. The network helps show where James N. Topper may publish in the future.

Co-authorship network of co-authors of James N. Topper

This figure shows the co-authorship network connecting the top 25 collaborators of James N. Topper. A scholar is included among the top collaborators of James N. Topper 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 James N. Topper. James N. Topper 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.
Smart, Nora G., Åsa Apelqvist, Xueying Gu, et al.. (2006). Conditional Expression of Smad7 in Pancreatic β Cells Disrupts TGF-β Signaling and Induces Reversible Diabetes Mellitus. PLoS Biology. 4(2). e39–e39. 104 indexed citations
2.
3.
Depre, C., et al.. (2003). Characterization of pDJA1, a cardiac-specific chaperone found by genomic profiling of the post-ischemic swine heart. Cardiovascular Research. 58(1). 126–135. 16 indexed citations
4.
Yang, Ruey‐Bing, et al.. (2003). A Novel Interleukin-17 Receptor-like Protein Identified in Human Umbilical Vein Endothelial Cells Antagonizes Basic Fibroblast Growth Factor-induced Signaling. Journal of Biological Chemistry. 278(35). 33232–33238. 82 indexed citations
5.
Tomlinson, James & James N. Topper. (2003). New insights into endothelial diversity. Current Atherosclerosis Reports. 5(3). 223–229. 4 indexed citations
6.
Wasserman, Scott M., Fuad Mehraban, László G. Kömüves, et al.. (2002). Gene expression profile of human endothelial cells exposed to sustained fluid shear stress. Physiological Genomics. 12(1). 13–23. 102 indexed citations
7.
Yang, Ruey‐Bing, Scott M. Wasserman, Steven D. Colman, et al.. (2002). Identification of a Novel Family of Cell-surface Proteins Expressed in Human Vascular Endothelium. Journal of Biological Chemistry. 277(48). 46364–46373. 132 indexed citations
8.
Feinberg, Mark W., Nicholas Sibinga, Philippe Wiesel, et al.. (2000). Transforming Growth Factor-β1 Inhibits Cytokine-mediated Induction of Human Metalloelastase in Macrophages. Journal of Biological Chemistry. 275(33). 25766–25773. 143 indexed citations
9.
Gimbrone, Michael A., James N. Topper, Tobi Nagel, Keith R. Anderson, & Guillermo García‐Cardeña. (2000). Endothelial Dysfunction, Hemodynamic Forces, and Atherogenesisa. Annals of the New York Academy of Sciences. 902(1). 230–240. 656 indexed citations breakdown →
10.
Jain, Mukesh K., Mark W. Feinberg, Nicholas Sibinga, et al.. (2000). Transforming Growth Factor-β1 Inhibition of Macrophage Activation Is Mediated via Smad3. Journal of Biological Chemistry. 275(47). 36653–36658. 146 indexed citations
11.
Topper, James N.. (2000). TGF-β in the Cardiovascular System. Trends in Cardiovascular Medicine. 10(3). 132–137. 44 indexed citations
13.
Topper, James N. & Michael A. Gimbrone. (1999). Blood flow and vascular gene expression: fluid shear stress as a modulator of endothelial phenotype. Molecular Medicine Today. 5(1). 40–46. 294 indexed citations
14.
Gimbrone, Michael A., Nitzan Resnick, Tobi Nagel, et al.. (1997). Hemodynamics, Endothelial Gene Expression, and Atherogenesisa. Annals of the New York Academy of Sciences. 811(1). 1–11. 93 indexed citations
15.
Hayashi, Hidetoshi, Yubin Qiu, Jiexing Cai, et al.. (1997). The MAD-Related Protein Smad7 Associates with the TGFβ Receptor and Functions as an Antagonist of TGFβ Signaling. Cell. 89(7). 1165–1173. 1158 indexed citations breakdown →
16.
Gimbrone, Michael A., Tobi Nagel, & James N. Topper. (1997). Biomechanical activation: an emerging paradigm in endothelial adhesion biology.. Journal of Clinical Investigation. 99(8). 1809–1813. 268 indexed citations
17.
Topper, James N., Jeffrey Bennett, & David A. Clayton. (1992). A role for RNAse MRP in mitochondrial RNA processing. Cell. 70(1). 16–20. 66 indexed citations
18.
Hsieh, Chih‐Lin, Tim Donlon, Basil T. Darras, et al.. (1990). The gene for the RNA component of the mitochondrial RNA-processing endoribonuclease is located on human chromosome 9p and on mouse chromosome 4. Genomics. 6(3). 540–544. 27 indexed citations
19.
Topper, James N. & David A. Clayton. (1990). Characterization of human MRP/Th RNA and its nuclear gene: full length MRP/Th RNA is an active endoribonuclease when assembled as an RNP. Nucleic Acids Research. 18(4). 793–799. 92 indexed citations
20.
Gold, H., James N. Topper, David A. Clayton, & Joe Craft. (1989). The RNA Processing Enzyme RNase MRP Is Identical to the Th RNP and Related to RNase P. Science. 245(4924). 1377–1380. 134 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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