Nathan D. Coles

855 total citations
17 papers, 608 citations indexed

About

Nathan D. Coles is a scholar working on Plant Science, Genetics and Agronomy and Crop Science. According to data from OpenAlex, Nathan D. Coles has authored 17 papers receiving a total of 608 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Plant Science, 12 papers in Genetics and 3 papers in Agronomy and Crop Science. Recurrent topics in Nathan D. Coles's work include Genetic Mapping and Diversity in Plants and Animals (11 papers), Genetics and Plant Breeding (10 papers) and Genetic and phenotypic traits in livestock (4 papers). Nathan D. Coles is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (11 papers), Genetics and Plant Breeding (10 papers) and Genetic and phenotypic traits in livestock (4 papers). Nathan D. Coles collaborates with scholars based in United States, Australia and Chile. Nathan D. Coles's co-authors include James B. Holland, Peter Balint‐Kurti, Michael D. McMullen, Richard C. Pratt, Mark Cooper, Carlos D. Messina, Zhanshan Dong, T. Abadie, Olga N. Danilevskaya and Matthew D. Krakowsky and has published in prestigious journals such as PLoS ONE, Genetics and Field Crops Research.

In The Last Decade

Nathan D. Coles

17 papers receiving 594 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nathan D. Coles United States	10	534	390	94	56	43	17	608
Delphine Van Inghelandt Germany	9	430 0.8×	320 0.8×	64 0.7×	48 0.9×	31 0.7×	13	519
Wubishet A. Bekele Canada	17	677 1.3×	428 1.1×	141 1.5×	152 2.7×	38 0.9×	34	794
J. J. Wassom United States	10	307 0.6×	163 0.4×	75 0.8×	72 1.3×	38 0.9×	14	355
Enrico Noli Italy	11	516 1.0×	223 0.6×	95 1.0×	45 0.8×	26 0.6×	21	558
Roma Rani Das India	18	799 1.5×	284 0.7×	82 0.9×	145 2.6×	43 1.0×	35	872
Gezahegn Girma United States	15	412 0.8×	245 0.6×	85 0.9×	112 2.0×	94 2.2×	23	545
Kassahun Bantte Ethiopia	13	530 1.0×	287 0.7×	50 0.5×	202 3.6×	34 0.8×	44	629
Yushen Dong China	11	714 1.3×	259 0.7×	134 1.4×	90 1.6×	13 0.3×	20	734
Charles Quigley United States	10	1.2k 2.3×	259 0.7×	124 1.3×	65 1.2×	16 0.4×	14	1.3k
Mark J. Millard United States	8	659 1.2×	568 1.5×	133 1.4×	73 1.3×	18 0.4×	9	777

Countries citing papers authored by Nathan D. Coles

Since Specialization

Citations

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

Fields of papers citing papers by Nathan D. Coles

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathan D. Coles. 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 Nathan D. Coles. The network helps show where Nathan D. Coles may publish in the future.

Co-authorship network of co-authors of Nathan D. Coles

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

All Works

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17 of 17 papers shown

Coles, Nathan D., Hua Mo, Jeffrey E. Habben, et al.. (2024). Transgene effects vary among maize populations with implications for improving quantitative traits. Crop Science. 65(1). 1 indexed citations

Coles, Nathan D., Carlos D. Messina, Tom Tang, et al.. (2023). Transgene by germplasm interactions can impact transgene evaluation. Crop Science. 63(4). 1988–1997. 3 indexed citations

Coles, Nathan D., Hua Mo, Jeffrey E. Habben, et al.. (2023). Methods for evaluating effects of transgenes for quantitative traits. Crop Science. 64(1). 141–148. 2 indexed citations

Schussler, Jeffrey R., Ben Weers, Jingrui Wu, et al.. (2022). Novel Genetic Variation Through Altered zmm28 Expression Improves Maize Performance Under Abiotic Stress. Field Crops Research. 281. 108486–108486. 5 indexed citations

Nelson, Paul, Matthew D. Krakowsky, Nathan D. Coles, et al.. (2015). Genetic Characterization of the North Carolina State University Maize Lines. Crop Science. 56(1). 259–275. 18 indexed citations

Pratt, Richard C., James B. Holland, Peter Balint‐Kurti, et al.. (2015). Registration of the Ki14 × B73 Recombinant Inbred Mapping Population of Maize. Journal of Plant Registrations. 9(2). 262–265. 1 indexed citations

Dong, Zhanshan, Olga N. Danilevskaya, T. Abadie, et al.. (2012). A Gene Regulatory Network Model for Floral Transition of the Shoot Apex in Maize and Its Dynamic Modeling. PLoS ONE. 7(8). e43450–e43450. 97 indexed citations

Browne, Chris, Nathan D. Coles, Magen S. Eller, et al.. (2011). The relationship between parental genetic or phenotypic divergence and progeny variation in the maize nested association mapping population. Heredity. 108(5). 490–499. 95 indexed citations

Coles, Nathan D., et al.. (2011). Allelic Effect Variation at Key Photoperiod Response Quantitative Trait Loci in Maize. Crop Science. 51(3). 1036–1049. 16 indexed citations

10.

Coles, Nathan D., et al.. (2011). Mapping QTL Controlling Southern Leaf Blight Resistance by Joint Analysis of Three Related Recombinant Inbred Line Populations. Crop Science. 51(4). 1571–1579. 32 indexed citations

11.

Holland, James B. & Nathan D. Coles. (2011). QTL Controlling Masculinization of Ear Tips in a Maize (Zea mays L.) Intraspecific Cross. G3 Genes Genomes Genetics. 1(5). 337–341. 6 indexed citations

12.

Zwonitzer, John C., Nathan D. Coles, Matthew D. Krakowsky, et al.. (2009). Mapping Resistance Quantitative Trait Loci for Three Foliar Diseases in a Maize Recombinant Inbred Line Population—Evidence for Multiple Disease Resistance?. Phytopathology. 100(1). 72–79. 93 indexed citations

13.

Coles, Nathan D., Michael D. McMullen, Peter Balint‐Kurti, Richard C. Pratt, & James B. Holland. (2009). Genetic Control of Photoperiod Sensitivity in Maize Revealed by Joint Multiple Population Analysis. Genetics. 184(3). 799–812. 113 indexed citations

14.

Coles, Nathan D.. (2009). The Genetic Architecture of Maize Photoperiod Sensitivity as Revealed by Recombinant Inbred Line, Backcross, and Heterogeneous Inbred Family Populations.. NCSU Libraries Repository (North Carolina State University Libraries). 3 indexed citations

15.

Nelson, Paul, Nathan D. Coles, James B. Holland, et al.. (2008). Molecular Characterization of Maize Inbreds with Expired U.S. Plant Variety Protection. Crop Science. 48(5). 1673–1685. 56 indexed citations

16.

Maughan, Peter J., Bożena Kolano, Jolanta Małuszyńska, et al.. (2006). Molecular and cytological characterization of ribosomal RNA genes inChenopodium quinoaandChenopodium berlandieri. Genome. 49(7). 825–839. 41 indexed citations

17.

Coles, Nathan D., Craig E. Coleman, Shawn A. Christensen, et al.. (2004). Development and use of an expressed sequenced tag library in quinoa (Chenopodium quinoa Willd.) for the discovery of single nucleotide polymorphisms. Plant Science. 168(2). 439–447. 26 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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