Greg May

1.1k total citations
11 papers, 744 citations indexed

About

Greg May is a scholar working on Plant Science, Molecular Biology and Computer Networks and Communications. According to data from OpenAlex, Greg May has authored 11 papers receiving a total of 744 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Plant Science, 2 papers in Molecular Biology and 1 paper in Computer Networks and Communications. Recurrent topics in Greg May's work include Agricultural pest management studies (2 papers), Soybean genetics and cultivation (2 papers) and Chromosomal and Genetic Variations (2 papers). Greg May is often cited by papers focused on Agricultural pest management studies (2 papers), Soybean genetics and cultivation (2 papers) and Chromosomal and Genetic Variations (2 papers). Greg May collaborates with scholars based in United States, Switzerland and India. Greg May's co-authors include Andrew Farmer, Marc Libault, Gary Stacey, Paul L. Auer, Jessica A. Schlueter, Scott A. Jackson, R. W. Doerge, Anne C. Roulin, W. Brad Barbazuk and Eliot M. Herman and has published in prestigious journals such as PLANT PHYSIOLOGY, The Plant Journal and BMC Bioinformatics.

In The Last Decade

Greg May

10 papers receiving 724 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Greg May United States 9 594 277 67 57 37 11 744
Guy Davenport United Kingdom 11 655 1.1× 391 1.4× 192 2.9× 48 0.8× 44 1.2× 18 814
Chun-Huai Cheng United States 12 613 1.0× 378 1.4× 68 1.0× 18 0.3× 21 0.6× 23 798
Çetin Yüceer United States 12 859 1.4× 714 2.6× 57 0.9× 76 1.3× 36 1.0× 16 1.1k
Isaak Tecle United States 7 632 1.1× 466 1.7× 149 2.2× 39 0.7× 28 0.8× 10 833
Shu‐Jen Wang Taiwan 16 607 1.0× 231 0.8× 37 0.6× 35 0.6× 24 0.6× 33 741
Milind B. Ratnaparkhe India 19 1.2k 1.9× 193 0.7× 127 1.9× 155 2.7× 27 0.7× 65 1.3k
Ethalinda K. S. Cannon United States 16 759 1.3× 430 1.6× 278 4.1× 25 0.4× 26 0.7× 31 997
Shen Bo China 14 439 0.7× 247 0.9× 112 1.7× 44 0.8× 19 0.5× 35 626
Daiqing Huang Canada 10 977 1.6× 545 2.0× 124 1.9× 23 0.4× 21 0.6× 14 1.1k
Suyun Wei China 11 180 0.3× 219 0.8× 82 1.2× 41 0.7× 11 0.3× 22 397

Countries citing papers authored by Greg May

Since Specialization
Citations

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

Fields of papers citing papers by Greg May

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Greg May. 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 Greg May. The network helps show where Greg May may publish in the future.

Co-authorship network of co-authors of Greg May

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

All Works

11 of 11 papers shown
1.
Livingstone, Donald, Stefan Royaert, Keithanne Mockaitis, et al.. (2015). Making a chocolate chip: development and evaluation of a 6K SNP array forTheobroma cacao. DNA Research. 22(4). 279–291. 28 indexed citations
2.
He, Ruifeng, Fernanda Salvato, Min-Jeong Kim, et al.. (2014). A systems-wide comparison of red rice (Oryza longistaminata) tissues identifies rhizome specific genes and proteins that are targets for cultivated rice improvement. BMC Plant Biology. 14(1). 46–46. 35 indexed citations
4.
He, Ruifeng, Minjeong Kim, William M. Nelson, et al.. (2012). Next‐generation sequencing‐based transcriptomic and proteomic analysis of the common reed, Phragmites australis (Poaceae), reveals genes involved in invasiveness and rhizome specificity. American Journal of Botany. 99(2). 232–247. 43 indexed citations
5.
Roulin, Anne C., Paul L. Auer, Marc Libault, et al.. (2012). The fate of duplicated genes in a polyploid plant genome. The Plant Journal. 73(1). 143–153. 233 indexed citations
6.
Close, Timothy J., Ming‐Cheng Luo, Stefano Lonardi, et al.. (2011). Genome Resources For Cowpea Genotype IT97K-499-35. e-Publications@Marquette (Marquette University). 1 indexed citations
7.
Kumar, Ashish, Anuja Dubey, Ashwin Prakash, et al.. (2011). Development and use of genic molecular markers (GMMs) for construction of a transcript map of chickpea (Cicer arietinum L.). Theoretical and Applied Genetics. 122(8). 1577–1589. 101 indexed citations
8.
9.
Joshi, Trupti, Zhe Yan, Marc Libault, et al.. (2010). Prediction of novel miRNAs and associated target genes in Glycine max. BMC Bioinformatics. 11(S1). S14–S14. 101 indexed citations
10.
Oard, James H., K. A. K. Moldenhauer, James C. Nelson, et al.. (2010). Registration of the MY2 ‘Cypress’/‘LaGrue’ Rice Recombinant Inbred Line Mapping Population. Journal of Plant Registrations. 4(3). 261–265. 7 indexed citations
11.
Gessler, Damian D. G., et al.. (2009). SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services. BMC Bioinformatics. 10(1). 309–309. 39 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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