Katherine E. Guill

2.3k total citations
10 papers, 582 citations indexed

About

Katherine E. Guill is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Katherine E. Guill has authored 10 papers receiving a total of 582 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Plant Science, 7 papers in Genetics and 4 papers in Molecular Biology. Recurrent topics in Katherine E. Guill's work include Genetic Mapping and Diversity in Plants and Animals (7 papers), Genetics and Plant Breeding (5 papers) and Genetic and phenotypic traits in livestock (3 papers). Katherine E. Guill is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (7 papers), Genetics and Plant Breeding (5 papers) and Genetic and phenotypic traits in livestock (3 papers). Katherine E. Guill collaborates with scholars based in United States, Germany and Japan. Katherine E. Guill's co-authors include Michael D. McMullen, Zhijie Liu, Joshua C. Stein, Apurva Narechania, Christopher A. Maher, Doreen Ware, Jer-Ming Chia, Sunita Kumari, Lifang Zhang and Jeffrey Ross‐Ibarra and has published in prestigious journals such as Genetics, PLoS Genetics and BMC Bioinformatics.

In The Last Decade

Katherine E. Guill

10 papers receiving 566 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Katherine E. Guill United States 8 496 222 201 31 26 10 582
Dadakhalandar Doddamani India 11 445 0.9× 120 0.5× 164 0.8× 10 0.3× 16 0.6× 17 577
Chengzhi Jiao China 11 531 1.1× 352 1.6× 193 1.0× 29 0.9× 126 4.8× 16 768
Daniel Fulop United States 6 260 0.5× 80 0.4× 181 0.9× 12 0.4× 12 0.5× 6 354
Brandt Cassidy United States 12 320 0.6× 102 0.5× 343 1.7× 14 0.5× 15 0.6× 14 606
Brigitte T. Hofmeister United States 10 535 1.1× 107 0.5× 463 2.3× 16 0.5× 10 0.4× 10 761
Bujie Zhan Denmark 5 287 0.6× 152 0.7× 120 0.6× 12 0.4× 29 1.1× 6 371
Minami Shimizu Japan 10 347 0.7× 56 0.3× 280 1.4× 10 0.3× 13 0.5× 20 507
Xiangchun Zhou China 13 603 1.2× 314 1.4× 182 0.9× 5 0.2× 34 1.3× 22 651
Xuelei Dai China 10 108 0.2× 152 0.7× 143 0.7× 28 0.9× 20 0.8× 16 294
Ulrike Ober Germany 5 238 0.5× 450 2.0× 54 0.3× 66 2.1× 38 1.5× 6 497

Countries citing papers authored by Katherine E. Guill

Since Specialization
Citations

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

Fields of papers citing papers by Katherine E. Guill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Katherine E. Guill. 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 Katherine E. Guill. The network helps show where Katherine E. Guill may publish in the future.

Co-authorship network of co-authors of Katherine E. Guill

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

All Works

10 of 10 papers shown
1.
Nelson, Sven, et al.. (2023). RootBot: High‐throughput root stress phenotyping robot. Applications in Plant Sciences. 11(6). e11541–e11541. 3 indexed citations
2.
Yang, Jinliang, Sofiane Mezmouk, Andy Baumgarten, et al.. (2021). Correction: Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize. PLoS Genetics. 17(9). e1009825–e1009825. 1 indexed citations
3.
Guill, Katherine E., et al.. (2019). Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs. BMC Plant Biology. 19(1). 412–412. 27 indexed citations
4.
Yang, Jinliang, Sofiane Mezmouk, Andy Baumgarten, et al.. (2017). Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize. PLoS Genetics. 13(9). e1007019–e1007019. 121 indexed citations
5.
Gerke, Justin, Jode W. Edwards, Katherine E. Guill, Jeffrey Ross‐Ibarra, & Michael D. McMullen. (2015). The Genomic Impacts of Drift and Selection for Hybrid Performance in Maize. Genetics. 201(3). 1201–1211. 39 indexed citations
6.
Liu, Zhengbin, Jason P. Cook, S. Melia-Hancock, et al.. (2015). Expanding Maize Genetic Resources with Predomestication Alleles: Maize–Teosinte Introgression Populations. The Plant Genome. 9(1). 44 indexed citations
7.
Zhao, Qiong, Allison Weber, Michael D. McMullen, Katherine E. Guill, & John Doebley. (2010). MADS-box genes of maize: frequent targets of selection during domestication. Genetics Research. 93(1). 65–75. 36 indexed citations
8.
Flint-García, Sherry, Katherine E. Guill, Héctor Sánchez‐Villeda, Steven Schroeder, & Michael D. McMullen. (2009). MAIZE AMINO ACID PATHWAYS MAINTAIN HIGH LEVELS OF GENETIC DIVERSITY. Maydica. 54(4). 375–386. 7 indexed citations
9.
Zhang, Lifang, Jer-Ming Chia, Sunita Kumari, et al.. (2009). A Genome-Wide Characterization of MicroRNA Genes in Maize. PLoS Genetics. 5(11). e1000716–e1000716. 291 indexed citations
10.
Sánchez‐Villeda, Héctor, Steven Schroeder, Sherry Flint-García, et al.. (2008). DNAAlignEditor: DNA alignment editor tool. BMC Bioinformatics. 9(1). 154–154. 13 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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2026