Thomas J. Sharpton

22.2k total citations · 2 hit papers
100 papers, 3.9k citations indexed

About

Thomas J. Sharpton is a scholar working on Molecular Biology, Ecology and Physiology. According to data from OpenAlex, Thomas J. Sharpton has authored 100 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Molecular Biology, 22 papers in Ecology and 14 papers in Physiology. Recurrent topics in Thomas J. Sharpton's work include Gut microbiota and health (50 papers), Diet and metabolism studies (11 papers) and Genomics and Phylogenetic Studies (11 papers). Thomas J. Sharpton is often cited by papers focused on Gut microbiota and health (50 papers), Diet and metabolism studies (11 papers) and Genomics and Phylogenetic Studies (11 papers). Thomas J. Sharpton collaborates with scholars based in United States, Canada and China. Thomas J. Sharpton's co-authors include Niklaus J. Grünwald, Zachary Foster, Katherine S. Pollard, Mariel M. Finucane, Christopher A. Gaulke, Timothy Laurent, Keaton Stagaman, Courtney R. Armour, Steven W. Kembel and James P. O’Dwyer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Thomas J. Sharpton

98 papers receiving 3.8k citations

Hit Papers

Metacoder: An R package f... 2014 2026 2018 2022 2017 2014 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas J. Sharpton United States 32 2.2k 897 603 425 349 100 3.9k
Suparna Mitra United Kingdom 21 2.2k 1.0× 1.4k 1.5× 520 0.9× 449 1.1× 328 0.9× 41 4.1k
Hans‐Joachim Ruscheweyh Switzerland 16 2.1k 0.9× 1.3k 1.4× 279 0.5× 446 1.0× 323 0.9× 36 3.8k
Antonio González Spain 28 2.0k 0.9× 637 0.7× 445 0.7× 595 1.4× 212 0.6× 94 4.2k
Dawn Ciulla United States 10 2.7k 1.2× 1.0k 1.1× 331 0.5× 493 1.2× 396 1.1× 13 4.4k
Anna Heintz‐Buschart Germany 31 2.4k 1.1× 660 0.7× 508 0.8× 668 1.6× 410 1.2× 77 4.3k
Diana Tabbaa United States 6 2.0k 0.9× 882 1.0× 268 0.4× 544 1.3× 282 0.8× 6 4.0k
Qiyun Zhu United States 30 2.4k 1.1× 730 0.8× 346 0.6× 269 0.6× 331 0.9× 72 3.9k
Giuseppe D’Auria Spain 30 2.3k 1.0× 1.5k 1.7× 281 0.5× 446 1.0× 288 0.8× 73 4.2k
Ilias Lagkouvardos Germany 33 2.7k 1.2× 770 0.9× 755 1.3× 223 0.5× 535 1.5× 71 4.4k
Mathangi Thiagarajan United States 13 2.1k 0.9× 569 0.6× 257 0.4× 570 1.3× 246 0.7× 18 3.4k

Countries citing papers authored by Thomas J. Sharpton

Since Specialization
Citations

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

Fields of papers citing papers by Thomas J. Sharpton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas J. Sharpton. 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 Thomas J. Sharpton. The network helps show where Thomas J. Sharpton may publish in the future.

Co-authorship network of co-authors of Thomas J. Sharpton

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas J. Sharpton. A scholar is included among the top collaborators of Thomas J. Sharpton 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 Thomas J. Sharpton. Thomas J. Sharpton 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.
Gaulke, Christopher A., Manuel García‐Jaramillo, Jeffrey T. Morré, et al.. (2024). Gut microbiota metabolically mediate intestinal helminth infection in zebrafish. mSystems. 9(9). e0054524–e0054524. 6 indexed citations
2.
Stagaman, Keaton, Kristin D. Kasschau, Vivek K. Unni, et al.. (2024). Effects of Paraquat, Dextran Sulfate Sodium, and Irradiation on Behavioral and Cognitive Performance and the Gut Microbiome in A53T and A53T-L444P Mice. Genes. 15(3). 282–282. 1 indexed citations
4.
Choi, Jaewoo, Robert Danczak, Carmen P. Wong, et al.. (2024). Gut enterotype-dependent modulation of gut microbiota and their metabolism in response to xanthohumol supplementation in healthy adults. Gut Microbes. 16(1). 2315633–2315633. 11 indexed citations
5.
Sharpton, Thomas J., Yuan Lü, Michael L. Kent, Stephen A. Watts, & Zoltán M. Varga. (2023). Tenth Aquatic Models of Human Disease Conference 2022 Workshop Report: Aquatics Nutrition and Reference Diet Development. Zebrafish. 20(6). 243–249. 2 indexed citations
6.
Drewery, Merritt L, Markita Savage, Zoltán M. Varga, et al.. (2023). Assessment of various standard fish diets on gut microbiome of platyfish Xiphophorus maculatus. Journal of Experimental Zoology Part B Molecular and Developmental Evolution. 342(3). 271–277. 2 indexed citations
7.
Humphreys, Ian R., Holly K. Arnold, Keaton Stagaman, et al.. (2023). Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations. Frontiers in Microbiology. 14. 1092216–1092216. 18 indexed citations
8.
Epstein, Hannah E., Kelly E. Speare, Thomas C. Adam, et al.. (2023). Microbiome ecological memory and responses to repeated marine heatwaves clarify variation in coral bleaching and mortality. Global Change Biology. 30(1). e17088–e17088. 11 indexed citations
9.
David, Maude M., Christine Tataru, L. Baker, et al.. (2022). Revealing General Patterns of Microbiomes That Transcend Systems: Potential and Challenges of Deep Transfer Learning. mSystems. 7(1). 5 indexed citations
10.
Gentekaki, Eleni, Justin Denny, Thomas J. Sharpton, et al.. (2022). The fecal microbiota of Thai school-aged children associated with demographic factors and diet. PeerJ. 10. e13325–e13325. 4 indexed citations
11.
Stagaman, Keaton, et al.. (2021). Diet and gut microbiome enterotype are associated at the population level in African buffalo. Nature Communications. 12(1). 2267–2267. 61 indexed citations
12.
Kent, Michael L., Elena S. Wall, Sophie R Sichel, et al.. (2021). Pseudocapillaria tomentosa , Mycoplasma spp., and Intestinal Lesions in Experimentally Infected Zebrafish Danio rerio. Zebrafish. 18(3). 207–220. 11 indexed citations
13.
Zhang, Yang, Gerd Bobe, Cristobal L. Miranda, et al.. (2021). Tetrahydroxanthohumol, a xanthohumol derivative, attenuates high-fat diet-induced hepatic steatosis by antagonizing PPARγ. eLife. 10. 12 indexed citations
14.
Flannery, Jessica, Keaton Stagaman, Adam R. Burns, et al.. (2020). Gut Feelings Begin in Childhood: the Gut Metagenome Correlates with Early Environment, Caregiving, and Behavior. mBio. 11(1). 54 indexed citations
15.
Sharpton, Thomas J., Svetlana Lyalina, Emily M. Deal, et al.. (2017). Development of Inflammatory Bowel Disease Is Linked to a Longitudinal Restructuring of the Gut Metagenome in Mice. mSystems. 2(5). 40 indexed citations
16.
Burns, Adam R., V Watral, Sophie R Sichel, et al.. (2017). Transmission of a common intestinal neoplasm in zebrafish by cohabitation. Journal of Fish Diseases. 41(4). 569–579. 22 indexed citations
17.
Kent, Michael L., et al.. (2016). Effects of Subclinical Mycobacterium chelonae Infections on Fecundity and Embryo Survival in Zebrafish. Zebrafish. 13(S1). S–88. 7 indexed citations
18.
Wong, Carmen P., et al.. (2016). Aging and serum MCP-1 are associated with gut microbiome composition in a murine model. PeerJ. 4. e1854–e1854. 80 indexed citations
19.
Sharpton, Thomas J., Samantha J. Riesenfeld, Steven W. Kembel, et al.. (2011). PhylOTU: A High-Throughput Procedure Quantifies Microbial Community Diversity and Resolves Novel Taxa from Metagenomic Data. PLoS Computational Biology. 7(1). e1001061–e1001061. 57 indexed citations
20.
Sharpton, Thomas J., et al.. (2006). Leveraging the Knowledge of Our Peers: Online Communities Hold the Promise to Enhance Scientific Research. PLoS Biology. 4(6). e199–e199. 3 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026