Kathryn S. Burch

2.0k citations
14 papers · 826 indexed · 1 hit paper · h-index 10
Topics
Genetic Associations and Epidemiology (12 papers)Genetic Mapping and Diversity in Plants and Animals (10 papers)Genetic and phenotypic traits in livestock (8 papers)

In The Last Decade

Kathryn S. Burch

14 papers receiving 816 citations

Hit Papers

Leveraging Polygenic Functional Enrichment to Improve GWA...20182026202020232018100200300400

Peers

Kathryn S. Burch
Comparison fields: 5 of 109
  • Genetics 514
  • Molecular Biology 309
  • Physiology 66
  • Immunology 63
  • Epidemiology 60
Replace Malika Freund with:
Malika Freund United States
Annalisa Buniello United Kingdom
Tomaz Berisa United States
Brooke N. Wolford United States
Armin Schoech United States
Longda Jiang Australia
Anuar Konkashbaev United States
Luke J. O’Connor United States
Peter VandeHaar United States
Jonathon LeFaive United States
Kathryn S. Burch relative to Malika Freund United States Malika Freund's profile →
Citations per field
00.5×1.5×
Malika Freund · 1×
Citations per year

Countries citing papers authored by Kathryn S. Burch

Since Specialization
Citations

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

Fields of papers citing papers by Kathryn S. Burch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kathryn S. Burch. 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 Kathryn S. Burch. The network helps show where Kathryn S. Burch may publish in the future.

Co-authorship network of co-authors of Kathryn S. Burch

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 12
2 6
3 56
4 7
5 21
6 18
7 8
8 46
9 28
10 1
11 59
12 13
13
Leveraging Polygenic Functional Enrichment to Improve GWAS Powerbreakdown →
485
14 66

About Kathryn S. Burch

Kathryn S. Burch is a scholar working on Developmental Biology, Genetics and Rheumatology, having authored 14 papers that have together received 826 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (12 papers), Genetic Mapping and Diversity in Plants and Animals (10 papers) and Genetic and phenotypic traits in livestock (8 papers). The work is most often cited by research in Genetics (514 citations), Molecular Biology (309 citations) and Aging (6 citations). Kathryn S. Burch has collaborated with scholars based in United States, Denmark and Finland. Frequent co-authors include Bogdan Paşaniuc, Malika Freund, Gleb Kichaev, Steven Gazal, Alkes L. Price, Gaurav Bhatia, Po‐Ru Loh, Armin Schoech, Sriram Sankararaman and Kangcheng Hou. Their work appears in journals such as Nature Communications, Nature Genetics and Bioinformatics.

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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