J. Moore

2.0k total citations · 1 hit paper
14 papers, 1.3k citations indexed

About

J. Moore is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism and Pharmacology. According to data from OpenAlex, J. Moore has authored 14 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Endocrinology, Diabetes and Metabolism and 4 papers in Pharmacology. Recurrent topics in J. Moore's work include Apelin-related biomedical research (4 papers), Hormonal Regulation and Hypertension (4 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (1 paper). J. Moore is often cited by papers focused on Apelin-related biomedical research (4 papers), Hormonal Regulation and Hypertension (4 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (1 paper). J. Moore collaborates with scholars based in United Kingdom, United States and Australia. J. Moore's co-authors include Nilesh J. Samani, John R. Thompson, Ian Ford, James Shepherd, Scott Brouilette, Chris J. Packard, Alex D. McMahon, Paul M. Stewart, Jeremy Tomlinson and Martin Hewison and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

J. Moore

13 papers receiving 1.3k citations

Hit Papers

Telomere length, risk of coronary heart disease, and stat... 2007 2026 2013 2019 2007 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Telomere length, risk of coronary heart disease, and statin treatment in the West of Scotland Primary Prevention Study: a nested case-control study
    2007 572 citations Scott Brouilette, J. Moore et al. The Lancet profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. Moore United Kingdom 13 568 407 357 159 129 14 1.3k
Sathishkumar Chandrakumar India 14 312 0.5× 288 0.7× 572 1.6× 44 0.3× 104 0.8× 16 1.2k
Jung Hye Kim South Korea 17 290 0.5× 288 0.7× 459 1.3× 46 0.3× 162 1.3× 37 1.3k
E Zukowska-Szczechowska Poland 21 234 0.4× 321 0.8× 480 1.3× 41 0.3× 143 1.1× 95 1.5k
Maria Teresa Gandolfo Italy 19 244 0.4× 151 0.4× 451 1.3× 20 0.1× 247 1.9× 39 1.6k
Jingyan Tian China 19 227 0.4× 275 0.7× 714 2.0× 22 0.1× 113 0.9× 47 1.4k
Rasmus Ribel‐Madsen Denmark 20 447 0.8× 285 0.7× 830 2.3× 40 0.3× 305 2.4× 41 1.4k
Nancy Hua United States 6 276 0.5× 261 0.6× 190 0.5× 50 0.3× 81 0.6× 8 877
Tjeerd Sijmonsma Germany 21 464 0.8× 234 0.6× 541 1.5× 15 0.1× 204 1.6× 27 1.4k
Michael Walter Germany 16 153 0.3× 163 0.4× 202 0.6× 27 0.2× 322 2.5× 43 937
Rana Malek United States 12 379 0.7× 238 0.6× 358 1.0× 11 0.1× 155 1.2× 40 1.1k

Countries citing papers authored by J. Moore

Since Specialization
Citations

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

Fields of papers citing papers by J. Moore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Moore. 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 J. Moore. The network helps show where J. Moore may publish in the future.

Co-authorship network of co-authors of J. Moore

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

All Works

14 of 14 papers shown
1.
2.
Morris, G E, Peter S. Braund, J. Moore, et al.. (2017). Coronary Artery Disease–Associated LIPA Coding Variant rs1051338 Reduces Lysosomal Acid Lipase Levels and Activity in Lysosomes. Arteriosclerosis Thrombosis and Vascular Biology. 37(6). 1050–1057. 27 indexed citations
3.
Moore, J., Kerry Woolnough, Gerald Langman, et al.. (2017). IRP2 as a potential modulator of cell proliferation, apoptosis and prognosis in nonsmall cell lung cancer. European Respiratory Journal. 49(4). 1600711–1600711. 25 indexed citations
4.
Bloomer, Lisa D.S., Christopher P. Nelson, James Eales, et al.. (2013). Male-Specific Region of the Y Chromosome and Cardiovascular Risk. Arteriosclerosis Thrombosis and Vascular Biology. 33(7). 1722–1727. 57 indexed citations
5.
Whittaker, Andrew K., J. Moore, Mariuca Vasa‐Nicotera, Suzanne Stevens, & N. J. Samani. (2008). Evidence for genetic regulation of endothelial progenitor cells and their role as biological markers of atherosclerotic susceptibility. European Heart Journal. 29(3). 332–338. 18 indexed citations
6.
Brouilette, Scott, J. Moore, Alex D. McMahon, et al.. (2007). Telomere length, risk of coronary heart disease, and statin treatment in the West of Scotland Primary Prevention Study: a nested case-control study. The Lancet. 369(9556). 107–114. 572 indexed citations breakdown →
7.
Quinkler, Marcus, Daniel Zehnder, Julia Lepenies, et al.. (2005). Expression of renal 11β-hydroxysteroid dehydrogenase type 2 is decreased in patients with impaired renal function. European Journal of Endocrinology. 153(2). 291–299. 34 indexed citations
8.
Boelaert, Kristien, Run Yu, Lesley Tannahill, et al.. (2004). PTTG’s C-terminal PXXP motifs modulate critical cellular processes in vitro. Journal of Molecular Endocrinology. 33(3). 663–677. 32 indexed citations
9.
Tomlinson, Jeremy, et al.. (2004). Weight Loss Increases 11β-Hydroxysteroid Dehydrogenase Type 1 Expression in Human Adipose Tissue. The Journal of Clinical Endocrinology & Metabolism. 89(6). 2711–2716. 73 indexed citations
10.
11.
Tomlinson, Jeremy, J. Moore, Mark S. Cooper, et al.. (2001). Regulation of Expression of 11β-Hydroxysteroid Dehydrogenase Type 1 in Adipose Tissue: Tissue-Specific Induction by Cytokines*. Endocrinology. 142(5). 1982–1989. 190 indexed citations
12.
Moore, J., John P. Monson, Gregory Kaltsas, et al.. (1999). Modulation of 11β-Hydroxysteroid Dehydrogenase Isozymes by Growth Hormone and Insulin-Like Growth Factor: In Vivo and In Vitro Studies1. The Journal of Clinical Endocrinology & Metabolism. 84(11). 4172–4177. 134 indexed citations
13.
Capocasale, Renold J., Roberta J. Lamb, Eric C. Vonderheid, et al.. (1995). Reduced surface expression of transforming growth factor beta receptor type II in mitogen-activated T cells from Sézary patients.. Proceedings of the National Academy of Sciences. 92(12). 5501–5505. 53 indexed citations
14.
Fox, Floyd E., Renold J. Capocasale, Henry C. Ford, et al.. (1992). Transforming growth factor-beta inhibits human T-cell proliferation through multiple targets.. PubMed. 11(6). 299–305. 30 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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