Tamara N. Dunn

1.1k total citations
17 papers, 810 citations indexed

About

Tamara N. Dunn is a scholar working on Physiology, Molecular Biology and Epidemiology. According to data from OpenAlex, Tamara N. Dunn has authored 17 papers receiving a total of 810 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Physiology, 8 papers in Molecular Biology and 6 papers in Epidemiology. Recurrent topics in Tamara N. Dunn's work include Diet and metabolism studies (8 papers), Adipose Tissue and Metabolism (6 papers) and Diet, Metabolism, and Disease (4 papers). Tamara N. Dunn is often cited by papers focused on Diet and metabolism studies (8 papers), Adipose Tissue and Metabolism (6 papers) and Diet, Metabolism, and Disease (4 papers). Tamara N. Dunn collaborates with scholars based in United States, United Kingdom and South Korea. Tamara N. Dunn's co-authors include Sean H. Adams, Peter J. Havel, Pieter J. Oort, Anthony P. Thomas, Bethany P. Cummings, Raymond R. Townsend, Nancy L. Keim, Kimber L. Stanhope, Karen L. Teff and Ryan W. Grant and has published in prestigious journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Brain Research.

In The Last Decade

Tamara N. Dunn

17 papers receiving 795 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tamara N. Dunn United States 13 515 306 302 262 102 17 810
S. Lambert-Porcheron France 15 525 1.0× 407 1.3× 225 0.7× 384 1.5× 231 2.3× 26 1.1k
Sandra Pereira Canada 14 449 0.9× 353 1.2× 142 0.5× 230 0.9× 59 0.6× 30 891
M. Gilbert United Kingdom 8 445 0.9× 123 0.4× 210 0.7× 262 1.0× 59 0.6× 12 702
B. H. Jones United States 12 428 0.8× 246 0.8× 201 0.7× 242 0.9× 140 1.4× 13 908
Marta Chacińska Poland 7 248 0.5× 308 1.0× 125 0.4× 201 0.8× 54 0.5× 8 700
Yuvaraj Mahendran Denmark 13 339 0.7× 377 1.2× 235 0.8× 188 0.7× 110 1.1× 22 881
Julie Takada Brazil 11 328 0.6× 122 0.4× 113 0.4× 241 0.9× 164 1.6× 12 777
Enchen Zhou China 14 446 0.9× 678 2.2× 84 0.3× 183 0.7× 90 0.9× 27 1.1k
Silvia Ezquerro Spain 11 380 0.7× 169 0.6× 92 0.3× 330 1.3× 66 0.6× 17 740
Joanna Karbowska Poland 17 330 0.6× 196 0.6× 138 0.5× 194 0.7× 61 0.6× 44 775

Countries citing papers authored by Tamara N. Dunn

Since Specialization
Citations

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

Fields of papers citing papers by Tamara N. Dunn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tamara N. Dunn

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

All Works

17 of 17 papers shown
1.
Kieffer, Dorothy A., Brian D. Piccolo, Maria L. Marco, et al.. (2016). Mice Fed a High-Fat Diet Supplemented with Resistant Starch Display Marked Shifts in the Liver Metabolome Concurrent with Altered Gut Bacteria. Journal of Nutrition. 146(12). 2476–2490. 50 indexed citations
2.
Kieffer, Dorothy A., Brian D. Piccolo, Maria L. Marco, et al.. (2016). Obese Mice Fed a Diet Supplemented with Enzyme-Treated Wheat Bran Display Marked Shifts in the Liver Metabolome Concurrent with Altered Gut Bacteria. Journal of Nutrition. 146(12). 2445–2460. 18 indexed citations
3.
Dunn, Tamara N., Tasuku Akiyama, Hyun Woo Lee, et al.. (2015). Evaluation of the Synuclein-γ (SNCG) Gene as a PPARγ Target in Murine Adipocytes, Dorsal Root Ganglia Somatosensory Neurons, and Human Adipose Tissue. PLoS ONE. 10(3). e0115830–e0115830. 12 indexed citations
4.
Dunn, Tamara N. & Sean H. Adams. (2014). Relations between Metabolic Homeostasis, Diet, and Peripheral Afferent Neuron Biology. Advances in Nutrition. 5(4). 386–393. 15 indexed citations
5.
Dunn, Tamara N., Alison H. Keenan, Anthony P. Thomas, John W. Newman, & Sean H. Adams. (2014). A diet containing a nonfat dry milk matrix significantly alters systemic oxylipins and the endocannabinoid 2-arachidonoylglycerol (2-AG) in diet-induced obese mice. Nutrition & Metabolism. 11(1). 24–24. 8 indexed citations
6.
Kieffer, Dorothy A., Roy J. Martin, Maria L. Marco, et al.. (2014). Resistant starch significantly alters gut microbiota and liver metabolome in mice fed a high fat diet (822.13). The FASEB Journal. 28(S1). 1 indexed citations
7.
Müller, Samuel, Raymond J. Carroll, Tamara N. Dunn, et al.. (2013). Structured variable selection with q-values. Biostatistics. 14(4). 695–707. 8 indexed citations
8.
Thomas, Anthony P., et al.. (2013). A dairy‐based high calcium diet improves glucose homeostasis and reduces steatosis in the context of preexisting obesity. Obesity. 21(3). E229–35. 21 indexed citations
9.
Lackey, Denise E., Christopher J. Lynch, Kristine C. Olson, et al.. (2013). Regulation of adipose branched-chain amino acid catabolism enzyme expression and cross-adipose amino acid flux in human obesity. American Journal of Physiology-Endocrinology and Metabolism. 304(11). E1175–E1187. 255 indexed citations
11.
Thomas, Anthony P., Tamara N. Dunn, Pieter J. Oort, Michel Grino, & Sean H. Adams. (2011). Inflammatory Phenotyping Identifies CD11d as a Gene Markedly Induced in White Adipose Tissue in Obese Rodents and Women. Journal of Nutrition. 141(6). 1172–1180. 31 indexed citations
12.
Purnell, Jonathan Q., Alexander A. Stevens, Peter J. Havel, et al.. (2010). Brain functional magnetic resonance imaging response to glucose and fructose infusions in humans. Diabetes Obesity and Metabolism. 13(3). 229–234. 65 indexed citations
13.
Floyd, Candace L., Tamara N. Dunn, Tsung‐Yu Chen, et al.. (2010). Dual inhibition of sodium-mediated proton and calcium efflux triggers non-apoptotic cell death in malignant gliomas. Brain Research. 1363. 159–169. 28 indexed citations
14.
Teff, Karen L., Raymond R. Townsend, Tamara N. Dunn, et al.. (2009). Endocrine and Metabolic Effects of Consuming Fructose- and Glucose-Sweetened Beverages with Meals in Obese Men and Women: Influence of Insulin Resistance on Plasma Triglyceride Responses. Endocrinology. 150(4). 2016–2016. 14 indexed citations
15.
Teff, Karen L., Raymond R. Townsend, Tamara N. Dunn, et al.. (2009). Endocrine and Metabolic Effects of Consuming Fructose- and Glucose-Sweetened Beverages with Meals in Obese Men and Women: Influence of Insulin Resistance on Plasma Triglyceride Responses. The Journal of Clinical Endocrinology & Metabolism. 94(5). 1562–1569. 221 indexed citations
16.
Oort, Pieter J., Trina A. Knotts, Michel Grino, et al.. (2008). γ-Synuclein Is an Adipocyte-Neuron Gene Coordinately Expressed with Leptin and Increased in Human Obesity , ,3. Journal of Nutrition. 138(5). 841–848. 26 indexed citations
17.
Halliwell, G., et al.. (1983). Microcolorimetric determination of soluble carbohydrates. Enzyme and Microbial Technology. 5(1). 37–40. 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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