Mary K. Kuhner

5.1k total citations · 3 hit papers
41 papers, 3.6k citations indexed

About

Mary K. Kuhner is a scholar working on Genetics, Molecular Biology and Surgery. According to data from OpenAlex, Mary K. Kuhner has authored 41 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Genetics, 22 papers in Molecular Biology and 9 papers in Surgery. Recurrent topics in Mary K. Kuhner's work include Genetic diversity and population structure (12 papers), Genomics and Phylogenetic Studies (10 papers) and Evolution and Genetic Dynamics (8 papers). Mary K. Kuhner is often cited by papers focused on Genetic diversity and population structure (12 papers), Genomics and Phylogenetic Studies (10 papers) and Evolution and Genetic Dynamics (8 papers). Mary K. Kuhner collaborates with scholars based in United States, France and Argentina. Mary K. Kuhner's co-authors include Joseph Felsenstein, Jon Yamato, Joe Felsenstein, G. Thomson, Sung-Hong Joe, Wendy P. Robinson, Lucian P. Smith, J Barbosa, Stephen S. Rich and Max P. Baur and has published in prestigious journals such as Nature Communications, Bioinformatics and Trends in Ecology & Evolution.

In The Last Decade

Mary K. Kuhner

40 papers receiving 3.5k citations

Hit Papers

A simulation comparison o... 1994 2026 2004 2015 1994 2006 1998 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mary K. Kuhner United States 19 2.4k 1.3k 742 428 346 41 3.6k
Urban Olsson Sweden 35 1.6k 0.7× 1.0k 0.8× 1.1k 1.5× 1.1k 2.6× 189 0.5× 130 3.8k
Mark Y. Stoeckle United States 30 1.7k 0.7× 2.7k 2.1× 1.7k 2.3× 799 1.9× 145 0.4× 59 5.4k
Manfred Grabherr Sweden 20 1.3k 0.6× 1.5k 1.2× 484 0.7× 418 1.0× 107 0.3× 45 3.1k
Keijo Viiri Finland 17 964 0.4× 1.7k 1.3× 841 1.1× 1.1k 2.6× 102 0.3× 34 3.7k
Derek E. Dimcheff United States 15 978 0.4× 979 0.7× 368 0.5× 255 0.6× 129 0.4× 25 2.3k
Scott K. Davis United States 34 2.0k 0.8× 948 0.7× 813 1.1× 735 1.7× 40 0.1× 92 3.6k
Georgia Tsagkogeorga United Kingdom 19 698 0.3× 1.0k 0.8× 619 0.8× 447 1.0× 99 0.3× 29 2.3k
Christopher Blair United States 19 896 0.4× 1.0k 0.8× 480 0.6× 1.1k 2.5× 58 0.2× 48 3.6k
Cathy C. Laurie United States 34 3.4k 1.4× 1.5k 1.2× 503 0.7× 807 1.9× 136 0.4× 63 5.3k
Jeffrey D. Jensen United States 45 3.8k 1.6× 1.9k 1.4× 599 0.8× 785 1.8× 52 0.2× 128 5.9k

Countries citing papers authored by Mary K. Kuhner

Since Specialization
Citations

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

Fields of papers citing papers by Mary K. Kuhner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mary K. Kuhner. 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 Mary K. Kuhner. The network helps show where Mary K. Kuhner may publish in the future.

Co-authorship network of co-authors of Mary K. Kuhner

This figure shows the co-authorship network connecting the top 25 collaborators of Mary K. Kuhner. A scholar is included among the top collaborators of Mary K. Kuhner 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 Mary K. Kuhner. Mary K. Kuhner 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
2.
Galipeau, Patricia C., Kenji Oman, Thomas G. Paulson, et al.. (2018). NSAID use and somatic exomic mutations in Barrett’s esophagus. Genome Medicine. 10(1). 17–17. 11 indexed citations
3.
Martinez, Pierre, Diego Mallo, Thomas G. Paulson, et al.. (2018). Evolution of Barrett’s esophagus through space and time at single-crypt and whole-biopsy levels. Nature Communications. 9(1). 794–794. 36 indexed citations
4.
Smith, Lucian P., Jon Yamato, & Mary K. Kuhner. (2018). CNValidator: validating somatic copy-number inference. Bioinformatics. 35(15). 2660–2662. 2 indexed citations
5.
Kostadinov, Rumen, Carlo C. Maley, & Mary K. Kuhner. (2016). Bulk Genotyping of Biopsies Can Create Spurious Evidence for Hetereogeneity in Mutation Content. PLoS Computational Biology. 12(4). e1004413–e1004413. 16 indexed citations
6.
Li, Xiaohong, Thomas G. Paulson, Patricia C. Galipeau, et al.. (2015). Assessment of Esophageal Adenocarcinoma Risk Using Somatic Chromosome Alterations in Longitudinal Samples in Barrett's Esophagus. Cancer Prevention Research. 8(9). 845–856. 34 indexed citations
7.
Kuhner, Mary K. & Jon Yamato. (2015). Assessing Differences Between Ancestral Recombination Graphs. Journal of Molecular Evolution. 80(5-6). 258–264. 3 indexed citations
8.
Zheng, Chaozhi, Mary K. Kuhner, & E. A. Thompson. (2014). Bayesian Inference of Local Trees Along Chromosomes by the Sequential Markov Coalescent. Journal of Molecular Evolution. 78(5). 279–292. 5 indexed citations
9.
Li, Xiaohong, Patricia C. Galipeau, Thomas G. Paulson, et al.. (2013). Temporal and Spatial Evolution of Somatic Chromosomal Alterations: A Case-Cohort Study of Barrett's Esophagus. Cancer Prevention Research. 7(1). 114–127. 105 indexed citations
10.
Kostadinov, Rumen, Mary K. Kuhner, Xiaohong Li, et al.. (2013). NSAIDs Modulate Clonal Evolution in Barrett's Esophagus. PLoS Genetics. 9(6). e1003553–e1003553. 56 indexed citations
11.
Kuhner, Mary K., et al.. (2013). GraphML specializations to codify ancestral recombinant graphs. Frontiers in Genetics. 4. 146–146. 9 indexed citations
12.
McCracken, Kevin G., Mariana Bulgarella, Kevin P. Johnson, et al.. (2009). Gene Flow in the Face of Countervailing Selection: Adaptation to High-Altitude Hypoxia in the  A Hemoglobin Subunit of Yellow-Billed Pintails in the Andes. Molecular Biology and Evolution. 26(4). 815–827. 67 indexed citations
13.
Kuhner, Mary K.. (2008). Coalescent genealogy samplers: windows into population history. Trends in Ecology & Evolution. 24(2). 86–93. 218 indexed citations
14.
Smith, Lucian P. & Mary K. Kuhner. (2008). The limits of fine‐scale mapping. Genetic Epidemiology. 33(4). 344–356. 6 indexed citations
15.
Kuhner, Mary K., Jon Yamato, & Joseph Felsenstein. (2000). Maximum Likelihood Estimation of Recombination Rates From Population Data. Genetics. 156(3). 1393–1401. 160 indexed citations
16.
Kuhner, Mary K. & Joseph Felsenstein. (2000). Sampling among haplotype resolutions in a coalescent-based genealogy sampler. Genetic Epidemiology. 19(S1). S15–S21. 15 indexed citations
17.
Kuhner, Mary K., Debbie A. Lawlor, P D Ennis, & Peter Parham. (1991). Gene conversion in the evolution of the human and chimpanzee MHC class I loci. Tissue Antigens. 38(4). 152–164. 45 indexed citations
18.
Kuhner, Mary K., et al.. (1990). Gene conversion in the evolution of both the H-2 and Qa class I genes of the murine major histocompatibility complex.. Genetics. 126(4). 1115–1126. 14 indexed citations
19.
Klitz, William, Mary K. Kuhner, Wendy P. Robinson, Michael S. Esposito, & Glenys Thomson. (1989). Clues to IDDM pathogenesis from genetic and serological traits in multiply affected families. Genetic Epidemiology. 6(1). 117–122. 3 indexed citations
20.
Thomson, G., Wendy P. Robinson, Mary K. Kuhner, Sung-Hong Joe, & William Klitz. (1989). HLA and insulin gene associations with IDDM. Genetic Epidemiology. 6(1). 155–160. 77 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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