Charles Pyke

9.9k total citations · 3 hit papers
75 papers, 7.1k citations indexed

About

Charles Pyke is a scholar working on Cancer Research, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Charles Pyke has authored 75 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Cancer Research, 27 papers in Molecular Biology and 23 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Charles Pyke's work include Protease and Inhibitor Mechanisms (28 papers), Diabetes Treatment and Management (23 papers) and Peptidase Inhibition and Analysis (14 papers). Charles Pyke is often cited by papers focused on Protease and Inhibitor Mechanisms (28 papers), Diabetes Treatment and Management (23 papers) and Peptidase Inhibition and Analysis (14 papers). Charles Pyke collaborates with scholars based in Denmark, United States and United Kingdom. Charles Pyke's co-authors include Keld Danø, Lotte Bjerre Knudsen, Elisabeth Ralfkiær, Leif R. Lund, Karl Tryggvason, John Rømer, Jens Eriksen, Peter Kristensen, Anna Secher and Helene Solberg and has published in prestigious journals such as Nature, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Charles Pyke

74 papers receiving 7.0k citations

Hit Papers

align trajectories

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.

The arcuate nucleus mediates GLP-1 receptor agonist liraglutide-dependent weight loss

2014 702 citations Anna Secher, Jacob Jelsing et al. profile →
GLP-1 Receptor Localization in Monkey and Human Tissue: Novel Distribution Revealed With Extensively Validated Monoclonal Antibody

2014 660 citations Charles Pyke, Rikke Kaae Kirk et al. profile →
A comprehensive spatio-cellular map of the human hypothalamus

2025 29 citations Henning Hvid, Lotte Bjerre Knudsen et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Charles Pyke Denmark	41	2.7k	2.4k	1.9k	1.7k	1.2k	75	7.1k
Stuart J. Frank United States	48	1.0k 0.4×	2.7k 1.1×	1.8k 0.9×	2.7k 1.6×	232 0.2×	144	7.1k
Lee S. Weinstein United States	55	557 0.2×	5.4k 2.3×	1.6k 0.9×	1.1k 0.6×	149 0.1×	184	10.4k
Ali Hafezi‐Moghadam United States	39	459 0.2×	2.6k 1.1×	858 0.4×	587 0.3×	632 0.5×	95	6.6k
Andrea Graziani Italy	34	430 0.2×	3.9k 1.6×	999 0.5×	465 0.3×	346 0.3×	97	7.3k
Nina Wettschureck Germany	37	418 0.2×	3.7k 1.5×	981 0.5×	379 0.2×	362 0.3×	87	6.7k
Tkachuk Va Russia	43	1.1k 0.4×	3.0k 1.3×	450 0.2×	275 0.2×	315 0.3×	337	6.0k
Lee Chao United States	55	677 0.3×	3.3k 1.4×	556 0.3×	734 0.4×	197 0.2×	208	7.9k
Anna Bagnato Italy	46	1.0k 0.4×	3.3k 1.4×	1.4k 0.7×	427 0.2×	364 0.3×	124	6.2k
Per Lindahl Sweden	33	1.5k 0.6×	5.5k 2.3×	1.2k 0.6×	154 0.1×	390 0.3×	74	9.2k
Adrian C. Herington Australia	46	825 0.3×	2.1k 0.9×	521 0.3×	2.8k 1.6×	155 0.1×	183	6.3k

Countries citing papers authored by Charles Pyke

Since Specialization

Citations

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

Fields of papers citing papers by Charles Pyke

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charles Pyke

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Pyke, Charles, et al.. (2024). A systematic evaluation of state-of-the-art deconvolution methods in spatial transcriptomics: insights from cardiovascular disease and chronic kidney disease. SHILAP Revista de lepidopterología. 4. 1352594–1352594. 4 indexed citations

Rolin, Bidda, et al.. (2023). The intestinal permeability marker FITC-dextran 4kDa should be dosed according to lean body mass in obese mice. Nutrition and Diabetes. 13(1). 1–1. 20 indexed citations

Ludwig, Mette Q., Wenwen Cheng, Desiree Gordian, et al.. (2021). A genetic map of the mouse dorsal vagal complex and its role in obesity. Nature Metabolism. 3(4). 530–545. 109 indexed citations

Farkas, Erzsébet, Anett Szilvásy‐Szabó, Morten G. Rasch, et al.. (2020). Distribution and ultrastructural localization of the glucagon-like peptide-1 receptor (GLP-1R) in the rat brain. Brain Structure and Function. 226(1). 225–245. 48 indexed citations

Christoffersen, Berit Østergaard, Rikke Bjerring Skyggebjerg, Anne Bugge, et al.. (2019). Long-acting CCK analogue NN9056 lowers food intake and body weight in obese Göttingen Minipigs. International Journal of Obesity. 44(2). 447–456. 24 indexed citations

Hansen, Henrik H., Katrine Fabricius, Pernille Barkholt, et al.. (2016). Long-Term Treatment with Liraglutide, a Glucagon-Like Peptide-1 (GLP-1) Receptor Agonist, Has No Effect on β-Amyloid Plaque Load in Two Transgenic APP/PS1 Mouse Models of Alzheimer’s Disease. PLoS ONE. 11(7). e0158205–e0158205. 45 indexed citations

Secher, Anna, Christian D. Kelstrup, Kilian W. Conde‐Frieboes, et al.. (2016). Analytic framework for peptidomics applied to large-scale neuropeptide identification. Nature Communications. 7(1). 11436–11436. 93 indexed citations

Hansen, Henrik H., Pernille Barkholt, Katrine Fabricius, et al.. (2015). The GLP-1 receptor agonist liraglutide reduces pathology-specific tau phosphorylation and improves motor function in a transgenic hTauP301L mouse model of tauopathy. Brain Research. 1634. 158–170. 77 indexed citations

Hansen, Henrik H., Katrine Fabricius, Pernille Barkholt, et al.. (2015). The GLP-1 Receptor Agonist Liraglutide Improves Memory Function and Increases Hippocampal CA1 Neuronal Numbers in a Senescence-Accelerated Mouse Model of Alzheimer’s Disease. Journal of Alzheimer s Disease. 46(4). 877–888. 155 indexed citations

10.

Pedersen, Mikkel W., Helle J. Jacobsen, Klaus Koefoed, et al.. (2010). Sym004: A Novel Synergistic Anti–Epidermal Growth Factor Receptor Antibody Mixture with Superior Anticancer Efficacy. Cancer Research. 70(2). 588–597. 174 indexed citations

11.

Pittet, Brigitte, Charles Pyke, D. Baetens, et al.. (2004). Active-site inactivated FVIIa decreases thrombosis and necrosis in a random skin flap model of acute ischemia. Journal of Surgical Research. 122(2). 263–273. 11 indexed citations

12.

Österholm, Cecilia, Zhongquan Qi, Jana Ekberg, et al.. (2001). Initial Inhibition of Tissue Factor Signalling Reduces Chronic Vascular Changes in Isogenic Rat Aortic Transplants. American Journal of Transplantation. 1(1). 29–37. 3 indexed citations

13.

Mandriota, Stefano J., et al.. (2000). Hypoxia-Inducible Angiopoietin-2 Expression Is Mimicked by Iodonium Compounds and Occurs in the Rat Brain and Skin in Response to Systemic Hypoxia and Tissue Ischemia. American Journal Of Pathology. 156(6). 2077–2089. 90 indexed citations

14.

Pyke, Charles, et al.. (1997). Proteoglycan Expression in the Normal Rat Kidney. Nephron. 77(4). 461–470. 39 indexed citations

15.

Nielsen, Boye Schnack, Susanne Timshel, Lars Kjeldsen, et al.. (1996). 92 kDa type IV collagenase (MMP-9) is expressed in neutrophils and macrophages but not in malignant epithelial cells in human colon cancer. International Journal of Cancer. 65(1). 57–62. 147 indexed citations

16.

Brünner, Nils, et al.. (1994). Urokinase plasminogen activator (uPA) and its type 1 inhibitor (PAI-1): Regulators of proteolysis during cancer invasion and prognostic parameters in Breast cancer. Cancer treatment and research. 71. 299–309. 27 indexed citations

17.

Rømer, John, Charles Pyke, Leif R. Lund, et al.. (1994). Expression of uPA and its receptor by both neoplastic and stromal cells during xenograft invasion. International Journal of Cancer. 57(4). 553–560. 48 indexed citations

18.

Rømer, John, Leif R. Lund, Jens Eriksen, et al.. (1994). The Receptor for Urokinase-type Plasminogen Activator is Expressed by Keratinocytes at the Leading Edge During Re-Epithelialization of Mouse Skin Wounds. Journal of Investigative Dermatology. 102(4). 519–522. 124 indexed citations

19.

Kristensen, Peter Lommer, et al.. (1990). Plasminogen activator inhibitor-type 1 in Lewis lung carcinoma. Histochemistry and Cell Biology. 93(6). 559–566. 63 indexed citations

20.

Eriksen, Jens, et al.. (1989). Plasminogen activator inhibitor (type-1) in rat adrenal medulla. Histochemistry and Cell Biology. 92(5). 377–383. 10 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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