Peter Zahradka

5.0k total citations
182 papers, 4.0k citations indexed

About

Peter Zahradka is a scholar working on Molecular Biology, Nutrition and Dietetics and Physiology. According to data from OpenAlex, Peter Zahradka has authored 182 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Molecular Biology, 62 papers in Nutrition and Dietetics and 42 papers in Physiology. Recurrent topics in Peter Zahradka's work include Fatty Acid Research and Health (46 papers), Adipose Tissue and Metabolism (26 papers) and Eicosanoids and Hypertension Pharmacology (20 papers). Peter Zahradka is often cited by papers focused on Fatty Acid Research and Health (46 papers), Adipose Tissue and Metabolism (26 papers) and Eicosanoids and Hypertension Pharmacology (20 papers). Peter Zahradka collaborates with scholars based in Canada, United States and Japan. Peter Zahradka's co-authors include Carla G. Taylor, K. Ebisuzaki, Harold M. Aukema, Laura Saward, Jaime L. Clark, Dawn E. Larson, Jennifer Enns, Vanessa DeClercq, Michael C. Moon and Tanja Winter and has published in prestigious journals such as PLoS ONE, American Journal of Clinical Nutrition and Journal of Agricultural and Food Chemistry.

In The Last Decade

Peter Zahradka

177 papers receiving 3.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Zahradka Canada 35 1.6k 909 818 590 484 182 4.0k
Miguel A. Lasunción Spain 42 2.1k 1.3× 698 0.8× 696 0.9× 521 0.9× 541 1.1× 164 6.0k
Pilar Ramos Spain 31 1.1k 0.7× 723 0.8× 758 0.9× 306 0.5× 684 1.4× 100 3.7k
Haiming Cao United States 22 2.2k 1.4× 488 0.5× 1.4k 1.7× 493 0.8× 1.2k 2.6× 40 4.3k
Soonkyu Chung United States 37 1.3k 0.8× 950 1.0× 1.3k 1.6× 244 0.4× 938 1.9× 102 3.5k
Jahangir Iqbal United States 40 1.9k 1.2× 527 0.6× 691 0.8× 566 1.0× 1.2k 2.5× 92 5.1k
Eun Ju Bae South Korea 28 1.7k 1.1× 966 1.1× 1.4k 1.7× 225 0.4× 1.4k 2.8× 80 4.7k
Xavier Palomer Spain 38 2.4k 1.5× 343 0.4× 1.6k 1.9× 569 1.0× 1.2k 2.6× 87 4.9k
Anna Nicolaou United Kingdom 43 1.7k 1.1× 901 1.0× 680 0.8× 121 0.2× 487 1.0× 144 5.1k
Ye-Shih Ho United States 36 2.5k 1.6× 472 0.5× 1.1k 1.3× 387 0.7× 339 0.7× 55 5.1k
David Bishop‐Bailey United Kingdom 42 3.1k 2.0× 345 0.4× 1.1k 1.4× 467 0.8× 536 1.1× 77 6.4k

Countries citing papers authored by Peter Zahradka

Since Specialization
Citations

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

Fields of papers citing papers by Peter Zahradka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Zahradka

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Zahradka. A scholar is included among the top collaborators of Peter Zahradka 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 Peter Zahradka. Peter Zahradka 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.
Bell, Rhonda C., Peter Zahradka, Michel Aliani, et al.. (2024). A Comparison of Dry Bean and Pea Consumption on Serum Cholesterol: A Randomized Controlled Trial in Adults with Mild Hypercholesterolemia. Journal of Nutrition. 154(11). 3375–3387.
2.
Taylor, Carla G., et al.. (2023). Reduced in vitro starch hydrolysis and in vivo glycemic effects after addition of soy presscake to corn tortillas. Journal of the Science of Food and Agriculture. 103(15). 7829–7835. 1 indexed citations
3.
4.
Sabbir, Mohammad Golam, Carla G. Taylor, & Peter Zahradka. (2020). Hypomorphic CAMKK2 in EA.hy926 endothelial cells causes abnormal transferrin trafficking, iron homeostasis and glucose metabolism. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1867(10). 118763–118763. 16 indexed citations
5.
Zahradka, Peter, et al.. (2020). Processing method modulates the effectiveness of black beans for lowering blood cholesterol in spontaneously hypertensive rats. Journal of the Science of Food and Agriculture. 101(2). 449–458. 7 indexed citations
6.
Hammad, Shatha, Peter Eck, Xiang Chen, et al.. (2019). Common Variants in Lipid Metabolism–Related Genes Associate with Fat Mass Changes in Response to Dietary Monounsaturated Fatty Acids in Adults with Abdominal Obesity. Journal of Nutrition. 149(10). 1749–1756. 9 indexed citations
7.
Yeganeh, Azadeh, et al.. (2016). Trans10, cis12 conjugated linoleic acid inhibits 3T3-L1 adipocyte adipogenesis by elevating β-catenin levels. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1861(4). 363–370. 18 indexed citations
8.
Caligiuri, Stephanie P. B., Tanja Winter, Carla G. Taylor, et al.. (2013). Dietary Linoleic Acid and α-Linolenic Acid Differentially Affect Renal Oxylipins and Phospholipid Fatty Acids in Diet-Induced Obese Rats. Journal of Nutrition. 143(9). 1421–1431. 56 indexed citations
9.
10.
Taylor, Carla G., et al.. (2012). Inhibition of smooth muscle cell proliferation by adiponectin requires proteolytic conversion to its globular form. Journal of Endocrinology. 215(1). 107–117. 12 indexed citations
11.
Mohankumar, Suresh K., Jennifer Enns, Jianheng Shen, et al.. (2012). Dietary supplementation oftrans-11-vaccenic acid reduces adipocyte size but neither aggravates nor attenuates obesity-mediated metabolic abnormalities infa/faZucker rats. British Journal Of Nutrition. 109(9). 1628–1636. 14 indexed citations
12.
DeClercq, Vanessa, Carla G. Taylor, & Peter Zahradka. (2011). Isomer-specific effects of conjugated linoleic acid on blood pressure, adipocyte size and function. British Journal Of Nutrition. 107(10). 1413–1421. 19 indexed citations
13.
Zahradka, Peter, et al.. (2011). Tyrosine kinase-independent activation of extracellular-regulated kinase (ERK) 1/2 by the insulin-like growth factor-1 receptor. Cellular Signalling. 23(4). 739–746. 22 indexed citations
14.
Enns, Jennifer, Carla G. Taylor, & Peter Zahradka. (2011). Variations in Adipokine GenesAdipoQ,Lep, andLepRAre Associated with Risk for Obesity-Related Metabolic Disease: The Modulatory Role of Gene-Nutrient Interactions. Journal of Obesity. 2011. 1–17. 63 indexed citations
15.
Junaid, Asad, et al.. (2006). Osteopontin localizes to the nucleus of 293 cells and associates with polo-like kinase-1. American Journal of Physiology-Cell Physiology. 292(2). C919–C926. 69 indexed citations
16.
17.
Zahradka, Peter, et al.. (2003). Activation of peroxisome proliferator-activated receptors α and γ1 inhibits human smooth muscle cell proliferation. Molecular and Cellular Biochemistry. 246(1-2). 105–110. 19 indexed citations
18.
Zahradka, Peter, et al.. (1998). Modulation of the Vascular Smooth Muscle Angiotensin Subtype 2 (AT2) Receptor by Angiotensin II. Biochemical and Biophysical Research Communications. 252(2). 476–480. 22 indexed citations
19.
Zahradka, Peter, et al.. (1995). PCR-based analysis of voltage-gated K+ channels in vascular smooth muscle. Molecular and Cellular Biochemistry. 145(1). 39–44. 7 indexed citations
20.
Zahradka, Peter. (1987). Probing DNA polymerase α with monoclonal antibodies. FEBS Letters. 212(2). 259–262. 5 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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