Jennifer M. Monk

2.1k total citations
72 papers, 1.7k citations indexed

About

Jennifer M. Monk is a scholar working on Nutrition and Dietetics, Epidemiology and Molecular Biology. According to data from OpenAlex, Jennifer M. Monk has authored 72 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Nutrition and Dietetics, 24 papers in Epidemiology and 17 papers in Molecular Biology. Recurrent topics in Jennifer M. Monk's work include Adipokines, Inflammation, and Metabolic Diseases (22 papers), Fatty Acid Research and Health (21 papers) and Gut microbiota and health (12 papers). Jennifer M. Monk is often cited by papers focused on Adipokines, Inflammation, and Metabolic Diseases (22 papers), Fatty Acid Research and Health (21 papers) and Gut microbiota and health (12 papers). Jennifer M. Monk collaborates with scholars based in Canada, United States and France. Jennifer M. Monk's co-authors include Lindsay E. Robinson, Krista A. Power, Robert S. Chapkin, Wenqing Wu, Danyelle M. Liddle, Dion Lepp, David N. McMurray, Tim Y. Hou, Brad R. Weeks and K. Peter Pauls and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Biochemical Journal.

In The Last Decade

Jennifer M. Monk

69 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jennifer M. Monk Canada 27 636 622 360 297 290 72 1.7k
Caroline E. Childs United Kingdom 25 777 1.2× 515 0.8× 469 1.3× 103 0.3× 200 0.7× 41 1.6k
Marı́a Isabel Torres Spain 27 465 0.7× 456 0.7× 192 0.5× 396 1.3× 314 1.1× 66 2.1k
Rachel Marion‐Letellier France 23 624 1.0× 631 1.0× 308 0.9× 231 0.8× 243 0.8× 46 1.9k
Eric A.F. van Tol Netherlands 25 582 0.9× 784 1.3× 395 1.1× 273 0.9× 228 0.8× 45 2.1k
Donna F. Vine Canada 28 565 0.9× 462 0.7× 438 1.2× 155 0.5× 304 1.0× 75 2.2k
Laura M’Rabet Netherlands 22 600 0.9× 617 1.0× 178 0.5× 312 1.1× 118 0.4× 32 1.8k
Junki Miyamoto Japan 21 341 0.5× 1.1k 1.8× 670 1.9× 136 0.5× 155 0.5× 41 1.9k
Moises Torres‐Gonzalez United States 17 287 0.5× 536 0.9× 294 0.8× 103 0.3× 188 0.6× 36 1.3k
Ingibjörg Harðardóttir Iceland 22 462 0.7× 501 0.8× 210 0.6× 344 1.2× 278 1.0× 55 1.7k
Stefania De Santis Italy 20 253 0.4× 590 0.9× 212 0.6× 159 0.5× 128 0.4× 48 1.5k

Countries citing papers authored by Jennifer M. Monk

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer M. Monk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jennifer M. Monk. 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 Jennifer M. Monk. The network helps show where Jennifer M. Monk may publish in the future.

Co-authorship network of co-authors of Jennifer M. Monk

This figure shows the co-authorship network connecting the top 25 collaborators of Jennifer M. Monk. A scholar is included among the top collaborators of Jennifer M. Monk 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 Jennifer M. Monk. Jennifer M. Monk 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.
Monk, Jennifer M., et al.. (2025). Dose-Dependent Effects of Short-Chain Fatty Acids on 3T3-L1 Adipocyte Adipokine Secretion and Metabolic Function. Nutrients. 17(3). 571–571. 1 indexed citations
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Monk, Jennifer M., et al.. (2023). Effects of Online Career Training Modules on Undergraduate STEM Students’ Career Readiness Perceptions. American Journal of Educational Research. 11(4). 214–224. 1 indexed citations
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Monk, Jennifer M., et al.. (2022). Effect of Optional Assessments on Student Engagement, Learning Approach, Stress, and Perceptions of Online Learning during COVID-19. International Journal of Higher Education. 11(5). 87–87. 5 indexed citations
9.
Monk, Jennifer M., Danyelle M. Liddle, William J. Muller, et al.. (2021). Fish oil supplementation increases expression of mammary tumor apoptosis mediators and reduces inflammation in an obesity-associated HER-2 breast cancer model. The Journal of Nutritional Biochemistry. 95. 108763–108763. 9 indexed citations
10.
Liddle, Danyelle M., et al.. (2020). Dietary long-chain n-3 PUFAs mitigate CD4+ T cell/adipocyte inflammatory interactions in co-culture models of obese adipose tissue. The Journal of Nutritional Biochemistry. 86. 108488–108488. 4 indexed citations
11.
Liu, Jiajie, Salma A. Abdelmagid, Jennifer M. Monk, et al.. (2017). Marine fish oil is more potent than plant-based n-3 polyunsaturated fatty acids in the prevention of mammary tumors. The Journal of Nutritional Biochemistry. 55. 41–52. 26 indexed citations
12.
Fan, Yang-Yi, Evelyn Callaway, Jennifer M. Monk, et al.. (2016). A New Model to Study the Role of Arachidonic Acid in Colon Cancer Pathophysiology. Cancer Prevention Research. 9(9). 750–757. 8 indexed citations
13.
Monk, Jennifer M., Dion Lepp, Wenqing Wu, et al.. (2015). Diets enriched with cranberry beans alter the microbiota and mitigate colitis severity and associated inflammation. The Journal of Nutritional Biochemistry. 28. 129–139. 94 indexed citations
14.
Monk, Jennifer M., et al.. (2015). The integrative role of leptin, oestrogen and the insulin family in obesity‐associated breast cancer: potential effects of exercise. Obesity Reviews. 16(6). 473–487. 76 indexed citations
15.
Monk, Jennifer M., Harmony F. Turk, Yang-Yi Fan, et al.. (2014). Antagonizing Arachidonic Acid-Derived Eicosanoids Reduces Inflammatory Th17 and Th1 Cell-Mediated Inflammation and Colitis Severity. Mediators of Inflammation. 2014. 1–14. 28 indexed citations
16.
Monk, Jennifer M., Tim Y. Hou, Harmony F. Turk, David N. McMurray, & Robert S. Chapkin. (2013). n3 PUFAs Reduce Mouse CD4+ T-Cell Ex Vivo Polarization into Th17 Cells. Journal of Nutrition. 143(9). 1501–1508. 50 indexed citations
17.
Monk, Jennifer M., Tim Y. Hou, Harmony F. Turk, et al.. (2012). Dietary n-3 Polyunsaturated Fatty Acids (PUFA) Decrease Obesity-Associated Th17 Cell-Mediated Inflammation during Colitis. PLoS ONE. 7(11). e49739–e49739. 81 indexed citations
18.
Monk, Jennifer M., Evelyn Callaway, Brad R. Weeks, et al.. (2011). Th17 Cell Accumulation Is Decreased during Chronic Experimental Colitis by (n-3) PUFA in Fat-1 Mice3. Journal of Nutrition. 142(1). 117–124. 57 indexed citations
19.
Monk, Jennifer M., Cynthia L. Richard, & Bill Woodward. (2011). A non-inflammatory form of immune competence prevails in acute pre-pubescent malnutrition: new evidence based on critical mRNA transcripts in the mouse. British Journal Of Nutrition. 107(9). 1249–1253. 8 indexed citations
20.
Steevels, Tessa A. M., Lyn M. Hillyer, Jennifer M. Monk, Megan Fisher, & Bill Woodward. (2009). Effector/memory T cells of the weanling mouse exhibit Type 2 cytokine polarization in vitro and in vivo in the advanced stages of acute energy deficit. The Journal of Nutritional Biochemistry. 21(6). 504–511. 11 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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