David E. Cook

2.7k total citations · 2 hit papers
29 papers, 1.7k citations indexed

About

David E. Cook is a scholar working on Plant Science, Molecular Biology and Cell Biology. According to data from OpenAlex, David E. Cook has authored 29 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Plant Science, 16 papers in Molecular Biology and 9 papers in Cell Biology. Recurrent topics in David E. Cook's work include Plant-Microbe Interactions and Immunity (13 papers), Plant Pathogens and Fungal Diseases (9 papers) and Chromosomal and Genetic Variations (7 papers). David E. Cook is often cited by papers focused on Plant-Microbe Interactions and Immunity (13 papers), Plant Pathogens and Fungal Diseases (9 papers) and Chromosomal and Genetic Variations (7 papers). David E. Cook collaborates with scholars based in United States, Netherlands and Germany. David E. Cook's co-authors include Bart P. H. J. Thomma, Carl H. Mesarich, Andrew F. Bent, Jun Huang, Adam M. Bayless, Kai Wang, Jiming Jiang, Xiaoli Guo, Sara Melito and Brian W. Diers and has published in prestigious journals such as Science, Nature Communications and PLANT PHYSIOLOGY.

In The Last Decade

David E. Cook

29 papers receiving 1.7k citations

Hit Papers

Copy Number Variation of Multiple Genes at Rhg1 Mediates ... 2012 2026 2016 2021 2012 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David E. Cook United States 16 1.5k 471 312 118 65 29 1.7k
Caroline S. Moffat Australia 17 1.1k 0.7× 335 0.7× 278 0.9× 59 0.5× 50 0.8× 40 1.2k
Ricardo Oliva Philippines 23 2.2k 1.5× 438 0.9× 493 1.6× 67 0.6× 79 1.2× 63 2.3k
Jun Guo China 28 1.8k 1.2× 747 1.6× 240 0.8× 52 0.4× 77 1.2× 68 1.9k
Joëlle Milazzo France 14 975 0.7× 535 1.1× 336 1.1× 215 1.8× 30 0.5× 25 1.2k
Patricia Manosalva United States 16 1.2k 0.8× 428 0.9× 128 0.4× 64 0.5× 107 1.6× 28 1.4k
Kerry F. Pedley United States 25 2.3k 1.5× 1.0k 2.2× 530 1.7× 96 0.8× 45 0.7× 46 2.4k
Yeon-Ki Kim South Korea 18 1.2k 0.8× 980 2.1× 191 0.6× 70 0.6× 48 0.7× 37 1.5k
Liangsheng Xu China 20 969 0.7× 382 0.8× 211 0.7× 109 0.9× 37 0.6× 42 1.1k
Martha C. Giraldo United States 13 1.7k 1.1× 652 1.4× 571 1.8× 52 0.4× 65 1.0× 17 1.9k
Joëlle Amselem France 20 1.0k 0.7× 472 1.0× 344 1.1× 85 0.7× 28 0.4× 28 1.2k

Countries citing papers authored by David E. Cook

Since Specialization
Citations

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

Fields of papers citing papers by David E. Cook

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David E. Cook

This figure shows the co-authorship network connecting the top 25 collaborators of David E. Cook. A scholar is included among the top collaborators of David E. Cook 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 David E. Cook. David E. Cook 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
1.
Torres, David E., Vittorio Tracanna, Gabriel L. Fiorin, et al.. (2024). Implications of the three-dimensional chromatin organization for genome evolution in a fungal plant pathogen. Nature Communications. 15(1). 1701–1701. 12 indexed citations
2.
Lin, Guifang, Jun Huang, Huakun Zheng, et al.. (2024). Using recurrent neural networks to detect supernumerary chromosomes in fungal strains causing blast diseases. NAR Genomics and Bioinformatics. 6(3). lqae108–lqae108. 2 indexed citations
3.
Zhang, Wei, et al.. (2024). Machine learning‐based identification of general transcriptional predictors for plant disease. New Phytologist. 245(2). 785–806. 2 indexed citations
4.
Liu, Sanzhen, Guifang Lin, Sowmya R. Ramachandran, et al.. (2023). Rapid mini‐chromosome divergence among fungal isolates causing wheat blast outbreaks in Bangladesh and Zambia. New Phytologist. 241(3). 1266–1276. 9 indexed citations
5.
Cook, David E., et al.. (2023). Epigenetic regulation of nuclear processes in fungal plant pathogens. PLoS Pathogens. 19(8). e1011525–e1011525. 8 indexed citations
6.
Zhang, Wei, et al.. (2022). Inferring functional communities from partially observed biological networks exploiting geometric topology and side information. Scientific Reports. 12(1). 10883–10883. 9 indexed citations
7.
Marla, Sandeep, Wenguang Zheng, Divya Mishra, et al.. (2022). CRISPR guides induce gene silencing in plants in the absence of Cas. Genome biology. 23(1). 6–6. 37 indexed citations
8.
Huang, Jun, et al.. (2022). CRISPR-Cas12a induced DNA double-strand breaks are repaired by multiple pathways with different mutation profiles in Magnaporthe oryzae. Nature Communications. 13(1). 7168–7168. 24 indexed citations
9.
Zhang, Wei, Jun Huang, & David E. Cook. (2021). Histone modification dynamics at H3K27 are associated with altered transcription of in planta induced genes in Magnaporthe oryzae. PLoS Genetics. 17(2). e1009376–e1009376. 52 indexed citations
11.
Zheng, Wenguang, et al.. (2020). CRISPR-Cas RNA Targeting Using Transient Cas13a Expression in Nicotiana benthamiana. Methods in molecular biology. 2170. 1–18. 4 indexed citations
12.
Cook, David E., et al.. (2020). A unique chromatin profile defines adaptive genomic regions in a fungal plant pathogen. eLife. 9. 31 indexed citations
13.
Zhang, Wei, Jason Corwin, Daniel Copeland, et al.. (2019). Plant–necrotroph co-transcriptome networks illuminate a metabolic battlefield. eLife. 8. 43 indexed citations
14.
Zhao, Peng, Ely Oliveira‐Garcia, Guifang Lin, et al.. (2019). Effector gene reshuffling involves dispensable mini-chromosomes in the wheat blast fungus. PLoS Genetics. 15(9). e1008272–e1008272. 80 indexed citations
15.
Cook, David E., Jose Espejo Valle-Inclán, Alice Pajoro, et al.. (2018). Long-Read Annotation: Automated Eukaryotic Genome Annotation Based on Long-Read cDNA Sequencing. PLANT PHYSIOLOGY. 179(1). 38–54. 40 indexed citations
16.
Seidl, Michael, David E. Cook, & Bart P. H. J. Thomma. (2016). Chromatin Biology Impacts Adaptive Evolution of Filamentous Plant Pathogens. PLoS Pathogens. 12(11). e1005920–e1005920. 31 indexed citations
17.
Thomma, Bart P. H. J., Michael Seidl, Xiaoqian Shi‐Kunne, et al.. (2015). Mind the gap; seven reasons to close fragmented genome assemblies. Fungal Genetics and Biology. 90. 24–30. 81 indexed citations
18.
Cook, David E., Adam M. Bayless, Kai Wang, et al.. (2014). Distinct Copy Number, Coding Sequence, and Locus Methylation Patterns UnderlieRhg1-Mediated Soybean Resistance to Soybean Cyst Nematode    . PLANT PHYSIOLOGY. 165(2). 630–647. 109 indexed citations
19.
Cook, David E., Tong Geon Lee, Xiaoli Guo, et al.. (2012). Copy Number Variation of Multiple Genes at Rhg1 Mediates Nematode Resistance in Soybean. Science. 338(6111). 1206–1209. 455 indexed citations breakdown →
20.
Melito, Sara, Adam L. Heuberger, David E. Cook, et al.. (2010). A nematode demographics assay in transgenic roots reveals no significant impacts of the Rhg1locus LRR-Kinase on soybean cyst nematode resistance. BMC Plant Biology. 10(1). 104–104. 66 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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