Stuart J. Macdonald

2.9k total citations
62 papers, 2.0k citations indexed

About

Stuart J. Macdonald is a scholar working on Genetics, Molecular Biology and Plant Science. According to data from OpenAlex, Stuart J. Macdonald has authored 62 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Genetics, 21 papers in Molecular Biology and 12 papers in Plant Science. Recurrent topics in Stuart J. Macdonald's work include Genetic diversity and population structure (20 papers), Genetic Mapping and Diversity in Plants and Animals (17 papers) and Genetic and phenotypic traits in livestock (12 papers). Stuart J. Macdonald is often cited by papers focused on Genetic diversity and population structure (20 papers), Genetic Mapping and Diversity in Plants and Animals (17 papers) and Genetic and phenotypic traits in livestock (12 papers). Stuart J. Macdonald collaborates with scholars based in United States, New Zealand and United Kingdom. Stuart J. Macdonald's co-authors include Anthony D. Long, Elizabeth G. King, David B. Goldstein, Ulrich Certa, David B. Goldstein, Scott D. Pletcher, Stephen C. Stearns, Linda Partridge, Mahul Chakraborty and J. J. Emerson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Stuart J. Macdonald

57 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stuart J. Macdonald United States 23 901 715 368 355 305 62 2.0k
Maja Tarailo‐Graovac Canada 20 945 1.0× 2.1k 3.0× 1.1k 2.9× 114 0.3× 180 0.6× 58 3.3k
Jing‐Tao Sun China 20 226 0.3× 677 0.9× 285 0.8× 486 1.4× 578 1.9× 69 1.7k
Mira Han United States 21 677 0.8× 1.3k 1.8× 619 1.7× 41 0.1× 240 0.8× 40 2.2k
Ted Brummel United States 9 222 0.2× 640 0.9× 79 0.2× 377 1.1× 491 1.6× 10 1.7k
Guochun Liao United States 23 407 0.5× 1.6k 2.2× 351 1.0× 77 0.2× 92 0.3× 26 2.7k
Jean-Philippe Parvy France 15 586 0.7× 762 1.1× 133 0.4× 98 0.3× 763 2.5× 19 2.0k
Giuseppe Gargiulo Italy 22 627 0.7× 842 1.2× 228 0.6× 40 0.1× 627 2.1× 74 1.8k
Alan D. Shirras United Kingdom 27 478 0.5× 823 1.2× 146 0.4× 109 0.3× 493 1.6× 45 1.8k
Dick J. Van der Horst Netherlands 28 526 0.6× 925 1.3× 198 0.5× 55 0.2× 792 2.6× 61 2.6k
Pablo Cabrero United Kingdom 26 278 0.3× 483 0.7× 91 0.2× 136 0.4× 451 1.5× 34 1.4k

Countries citing papers authored by Stuart J. Macdonald

Since Specialization
Citations

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

Fields of papers citing papers by Stuart J. Macdonald

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stuart J. Macdonald. 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 Stuart J. Macdonald. The network helps show where Stuart J. Macdonald may publish in the future.

Co-authorship network of co-authors of Stuart J. Macdonald

This figure shows the co-authorship network connecting the top 25 collaborators of Stuart J. Macdonald. A scholar is included among the top collaborators of Stuart J. Macdonald 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 Stuart J. Macdonald. Stuart J. Macdonald 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
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Chiu, Annie Ting Gee, Mark F. Bennett, Amy Schneider, et al.. (2025). Pathogenic Variants in RNU2‐2 , a Non‐coding Spliceosomal RNA , Cause a Distinctive Developmental and Epileptic Encephalopathy. Annals of Neurology. 99(1). 51–58. 1 indexed citations
3.
Macdonald, Stuart J., et al.. (2025). Dynamic changes in gene expression through aging in Drosophila melanogaster heads. G3 Genes Genomes Genetics. 15(4).
4.
Macdonald, Stuart J., et al.. (2024). Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster. G3 Genes Genomes Genetics. 14(3).
5.
Macdonald, Stuart J., et al.. (2023). The genetic basis of adaptation to copper pollution in Drosophila melanogaster. Frontiers in Genetics. 14. 1144221–1144221. 5 indexed citations
6.
Macdonald, Stuart J. & Anthony D. Long. (2022). Discovery of malathion resistance QTL in Drosophila melanogaster using a bulked phenotyping approach. G3 Genes Genomes Genetics. 12(12). 4 indexed citations
7.
Macdonald, Stuart J., et al.. (2022). Powerful, efficient QTL mapping in Drosophila melanogaster using bulked phenotyping and pooled sequencing. Genetics. 220(3). 2 indexed citations
8.
Tasnim, Sadia, et al.. (2022). Genetic variation in P-element dysgenic sterility is associated with double-strand break repair and alternative splicing of TE transcripts. PLoS Genetics. 18(12). e1010080–e1010080. 2 indexed citations
9.
Monnahan, Patrick J., Jack M. Colicchio, Lila Fishman, Stuart J. Macdonald, & John K. Kelly. (2021). Predicting evolutionary change at the DNA level in a natural Mimulus population. PLoS Genetics. 17(1). e1008945–e1008945. 9 indexed citations
10.
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Macdonald, Stuart J., et al.. (2020). A naturally-occurring 22-bp coding deletion in Ugt86Dd reduces nicotine resistance in Drosophila melanogaster. BMC Research Notes. 13(1). 188–188. 4 indexed citations
12.
Chakraborty, Mahul, J. J. Emerson, Stuart J. Macdonald, & Anthony D. Long. (2019). Structural variants exhibit widespread allelic heterogeneity and shape variation in complex traits. Nature Communications. 10(1). 4872–4872. 117 indexed citations
13.
Wang, Xiaofei, et al.. (2017). Naturally Segregating Variation at Ugt86Dd Contributes to Nicotine Resistance in Drosophila melanogaster. Genetics. 207(1). 311–325. 16 indexed citations
14.
Windham, Michael D., et al.. (2017). Can asexuality confer a short‐term advantage? Investigating apparent biogeographic success in the apomictic triploid fern Myriopteris gracilis. American Journal of Botany. 104(8). 1254–1265. 7 indexed citations
15.
Wang, Xiaofei, et al.. (2016). Mapping QTL Contributing to Variation in Posterior Lobe Morphology between Strains of Drosophila melanogaster. PLoS ONE. 11(9). e0162573–e0162573. 5 indexed citations
16.
Long, Anthony D., Stuart J. Macdonald, & Elizabeth G. King. (2014). Dissecting complex traits using the Drosophila Synthetic Population Resource. Trends in Genetics. 30(11). 488–495. 57 indexed citations
17.
King, Elizabeth G., et al.. (2014). Genetic Dissection of the Drosophila melanogaster Female Head Transcriptome Reveals Widespread Allelic Heterogeneity. PLoS Genetics. 10(5). e1004322–e1004322. 44 indexed citations
18.
Gruber, Jonathan D., Anne Génissel, Stuart J. Macdonald, & Anthony D. Long. (2007). How Repeatable Are Associations Between Polymorphisms in achaete–scute and Bristle Number Variation in Drosophila?. Genetics. 175(4). 1987–1997. 24 indexed citations
19.
20.
Pletcher, Scott D., Stuart J. Macdonald, Ulrich Certa, et al.. (2002). Genome-Wide Transcript Profiles in Aging and Calorically Restricted Drosophila melanogaster. Current Biology. 12(9). 712–723. 430 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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