Dawn M. Fedor

618 total citations
18 papers, 494 citations indexed

About

Dawn M. Fedor is a scholar working on Nutrition and Dietetics, Molecular Biology and Epidemiology. According to data from OpenAlex, Dawn M. Fedor has authored 18 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Nutrition and Dietetics, 8 papers in Molecular Biology and 7 papers in Epidemiology. Recurrent topics in Dawn M. Fedor's work include Fatty Acid Research and Health (9 papers), Liver Disease Diagnosis and Treatment (5 papers) and Diet, Metabolism, and Disease (4 papers). Dawn M. Fedor is often cited by papers focused on Fatty Acid Research and Health (9 papers), Liver Disease Diagnosis and Treatment (5 papers) and Diet, Metabolism, and Disease (4 papers). Dawn M. Fedor collaborates with scholars based in United States, China and Netherlands. Dawn M. Fedor's co-authors include Darshan S. Kelley, Yuriko Adkins, Bruce E. Mackey, David Siegel, Madhuri Vemuri, Ryan M. Kramer, John W. Newman, Iwan W. Schie, Ping Zhou and Jian Wu and has published in prestigious journals such as Journal of Nutrition, Antimicrobial Agents and Chemotherapy and European Journal of Immunology.

In The Last Decade

Dawn M. Fedor

18 papers receiving 483 citations

Peers

Dawn M. Fedor

PHYSI

EPIDE

EDM

Johanne Marin Canada

Jolene McMonagle Ireland

Brian R. Barrows United States

Christine M. Williams United Kingdom

M. Miriam Jacome‐Sosa Canada

Bénédicte Allam‐Ndoul Canada

Véronique Garneau Canada

Sara L. Svahn Sweden

Xian Yang China

E. Amusquivar Spain

Johanne Marin Canada

Dawn M. Fedor

284 ×1.2

123 ×0.9

PHYSI

49 ×0.4

EPIDE

143 ×1.2

59 ×0.5

EDM

Citations per year, relative to Dawn M. Fedor Dawn M. Fedor (= 1×) peers Johanne Marin

Countries citing papers authored by Dawn M. Fedor

Since Specialization

Citations

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

Fields of papers citing papers by Dawn M. Fedor

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dawn M. Fedor

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

All Works

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18 of 18 papers shown

Archer, Michelle, Hong Liang, Dawn M. Fedor, et al.. (2023). Stressed stability and protective efficacy of lead lyophilized formulations of ID93+GLA-SE tuberculosis vaccine. Heliyon. 9(6). e17325–e17325. 1 indexed citations

Kramer, Ryan M., Michelle Archer, Mark T. Orr, et al.. (2018). Development of a thermostable nanoemulsion adjuvanted vaccine against tuberculosis using a design-of-experiments approach. International Journal of Nanomedicine. Volume 13. 3689–3711. 30 indexed citations

Thompson, George R., Charles R. Krois, Verena K. Affolter, et al.. (2018). Examination of Fluconazole-Induced Alopecia in an Animal Model and Human Cohort. Antimicrobial Agents and Chemotherapy. 63(2). 7 indexed citations

Adkins, Yuriko, Theresa L. Pedersen, Dawn M. Fedor, et al.. (2017). Dietary Docosahexaenoic Acid and trans‐10, cis‐12‐Conjugated Linoleic Acid Differentially Alter Oxylipin Profiles in Mouse Periuterine Adipose Tissue. Lipids. 52(5). 399–413. 10 indexed citations

Chan, Michelle Y., et al.. (2016). Interactions Between Antigens and Nanoemulsion Adjuvants: Separation and Characterization Techniques. Methods in molecular biology. 1494. 285–294. 1 indexed citations

Chan, Michelle Y., et al.. (2016). Staining and Transfer Techniques for SDS-PAGE Gels to Minimize Oil-in-Water Emulsion Adjuvant Interference. Methods in molecular biology. 1494. 273–283. 7 indexed citations

Fedor, Dawn M., Simon H. Williams, Quinton M. Dowling, et al.. (2016). Lyophilization of an Adjuvanted Mycobacterium tuberculosis Vaccine in a Single-Chamber Pharmaceutical Cartridge. AAPS PharmSciTech. 18(6). 2077–2084. 4 indexed citations

Thompson, George R., Charles R. Krois, Verena K. Affolter, et al.. (2016). Retinoic Acid Is Not Involved in Fluconazole-Induced Alopecia: Evaluation in a Human Cohort and Rat Model. Open Forum Infectious Diseases. 3(suppl_1). 1 indexed citations

Adkins, Yuriko, Dawn M. Fedor, Bruce E. Mackey, Jian Wu, & Darshan S. Kelley. (2015). Dietary docosahexaenoic acid reverses nonalcoholic steatohepatitis and fibrosis caused by conjugated linoleic acid supplementation in mice. Journal of Functional Foods. 20. 443–452. 3 indexed citations

10.

Shichiri, Mototada, Yuriko Adkins, Noriko Ishida, et al.. (2014). DHA concentration of red blood cells is inversely associated with markers of lipid peroxidation in men taking DHA supplement. Journal of Clinical Biochemistry and Nutrition. 55(3). 196–202. 7 indexed citations

11.

Goverse, Gera, Brenda J. Olivier, Rosalie Molenaar, et al.. (2014). Vitamin A metabolism and mucosal immune function are distinct between BALB/c and C57BL/6 mice. European Journal of Immunology. 45(1). 89–100. 25 indexed citations

12.

Adkins, Yuriko, Iwan W. Schie, Dawn M. Fedor, et al.. (2013). A novel mouse model of nonalcoholic steatohepatitis with significant insulin resistance. Laboratory Investigation. 93(12). 1313–1322. 31 indexed citations

13.

Fedor, Dawn M., Yuriko Adkins, John W. Newman, Bruce E. Mackey, & Darshan S. Kelley. (2012). The Effect of Docosahexaenoic Acid on t 10, c 12-Conjugated Linoleic Acid-Induced Changes in Fatty Acid Composition of Mouse Liver, Adipose, and Muscle. Metabolic Syndrome and Related Disorders. 11(1). 63–70. 12 indexed citations

14.

Fedor, Dawn M., Yuriko Adkins, Bruce E. Mackey, & Darshan S. Kelley. (2012). Docosahexaenoic Acid Prevents Trans -10, Cis -12–Conjugated Linoleic Acid-Induced Nonalcoholic Fatty Liver Disease in Mice by Altering Expression of Hepatic Genes Regulating Fatty Acid Synthesis and Oxidation. Metabolic Syndrome and Related Disorders. 10(3). 175–180. 18 indexed citations

15.

Fedor, Dawn M. & Darshan S. Kelley. (2009). Prevention of insulin resistance by n-3 polyunsaturated fatty acids. Current Opinion in Clinical Nutrition & Metabolic Care. 12(2). 138–146. 191 indexed citations

16.

Kelley, Darshan S., David Siegel, Dawn M. Fedor, Yuriko Adkins, & Bruce E. Mackey. (2009). DHA Supplementation Decreases Serum C-Reactive Protein and Other Markers of Inflammation in Hypertriglyceridemic Men. Journal of Nutrition. 139(3). 495–501. 107 indexed citations

17.

Kelley, Darshan S., et al.. (2008). Flaxseed oil prevents trans-10, cis-12-conjugated linoleic acid-induced insulin resistance in mice. British Journal Of Nutrition. 101(5). 701–708. 38 indexed citations

18.

Fedor, Dawn M., et al.. (2008). Dietary Supplementation With Omega-3 Polyunsaturated Fatty Acids. 34(3). 1–4. 1 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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