Don C. Jones

6.2k total citations
165 papers, 2.5k citations indexed

About

Don C. Jones is a scholar working on Plant Science, Endocrinology and Molecular Biology. According to data from OpenAlex, Don C. Jones has authored 165 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 156 papers in Plant Science, 39 papers in Endocrinology and 10 papers in Molecular Biology. Recurrent topics in Don C. Jones's work include Research in Cotton Cultivation (147 papers), Plant and Fungal Interactions Research (39 papers) and Plant Virus Research Studies (33 papers). Don C. Jones is often cited by papers focused on Research in Cotton Cultivation (147 papers), Plant and Fungal Interactions Research (39 papers) and Plant Virus Research Studies (33 papers). Don C. Jones collaborates with scholars based in United States, China and Brazil. Don C. Jones's co-authors include Fred M. Bourland, Baohong Zhang, Runrun Sun, Jinfa Zhang, Richard G. Percy, Fuliang Xie, Qinglian Wang, Ping Zheng, Taein Lee and Sook Jung and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

Don C. Jones

151 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Don C. Jones United States 29 2.2k 728 385 104 101 165 2.5k
Yuanda Lv China 24 1.5k 0.7× 792 1.1× 141 0.4× 88 0.8× 260 2.6× 67 1.9k
Maojun Wang China 27 1.9k 0.9× 1.1k 1.5× 293 0.8× 19 0.2× 166 1.6× 61 2.3k
Fuguang Li China 40 3.8k 1.8× 2.4k 3.4× 152 0.4× 27 0.3× 129 1.3× 160 4.5k
Zhongxu Lin China 29 2.6k 1.2× 512 0.7× 670 1.7× 22 0.2× 316 3.1× 114 2.8k
Zhongli Zhou China 28 1.6k 0.7× 726 1.0× 120 0.3× 34 0.3× 95 0.9× 80 1.8k
Chaoyou Pang China 29 1.8k 0.8× 973 1.3× 131 0.3× 63 0.6× 113 1.1× 89 2.1k
Hǎihóng Shāng China 24 1.3k 0.6× 499 0.7× 122 0.3× 13 0.1× 65 0.6× 89 1.5k
Qian‐Hao Zhu Australia 40 4.1k 1.9× 3.0k 4.1× 382 1.0× 17 0.2× 425 4.2× 154 5.2k
Wànkuí Gǒng China 22 1.1k 0.5× 418 0.6× 114 0.3× 19 0.2× 158 1.6× 65 1.4k
Shoupu He China 22 1.5k 0.7× 641 0.9× 169 0.4× 10 0.1× 84 0.8× 108 1.7k

Countries citing papers authored by Don C. Jones

Since Specialization
Citations

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

Fields of papers citing papers by Don C. Jones

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Don C. Jones. 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 Don C. Jones. The network helps show where Don C. Jones may publish in the future.

Co-authorship network of co-authors of Don C. Jones

This figure shows the co-authorship network connecting the top 25 collaborators of Don C. Jones. A scholar is included among the top collaborators of Don C. Jones 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 Don C. Jones. Don C. Jones 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.
Smith, Linda J., Warwick N. Stiller, Gunjan Pandey, et al.. (2025). Comparative Genomics Reveals Ancient and Unique Pathogenicity Features in Australian Fusarium oxysporum f. sp. vasinfectum. Journal of Fungi. 11(7). 481–481.
2.
Bourland, Fred M. & Don C. Jones. (2024). Registration of Arkot 1102ne cotton germplasm line. Journal of Plant Registrations. 18(1). 134–141. 1 indexed citations
3.
Lubbers, Edward L., et al.. (2024). Registration of CA 4011 cotton germplasm line with resistance to areolate mildew and tolerance to thrips. Journal of Plant Registrations. 18(3). 556–563. 1 indexed citations
4.
Bourland, Fred M., et al.. (2024). Registration of Arkot 1202, Arkot 1207, Arkot 1208, and Arkot 1214 cotton germplasm lines. Journal of Plant Registrations. 18(2). 402–409. 2 indexed citations
5.
Kim, Hee Jin, Gregory N. Thyssen, Christopher D. Delhom, et al.. (2024). Genome-wide association studies of bundle and single fiber length traits reveal the genetic basis of within-sample variation in upland cotton fiber length. Frontiers in Plant Science. 15. 1472675–1472675. 4 indexed citations
6.
Fang, Hui, Priyanka Tyagi, Fred M. Bourland, et al.. (2024). Genome-wide association study of fiber quality traits in US upland cotton (Gossypium hirsutum L.). Theoretical and Applied Genetics. 137(9). 214–214. 2 indexed citations
7.
8.
Bourland, Fred M. & Don C. Jones. (2023). Registration of Arkot 1112, Arkot 1114, and Arkot 1115 cotton germplasm lines. Journal of Plant Registrations. 17(3). 544–550. 1 indexed citations
9.
Fang, David D., Gregory N. Thyssen, Maojun Wang, et al.. (2022). Genomic confirmation of Gossypium barbadense introgression into G. hirsutum and a subsequent MAGIC population. Molecular Genetics and Genomics. 298(1). 143–152. 6 indexed citations
10.
Jenkins, Johnie N., Jack C. McCarty, Martin J. Wubben, et al.. (2021). Registration of seven recombinant inbred lines of upland cotton with improved fiber length or strength. Journal of Plant Registrations. 16(1). 94–99. 1 indexed citations
11.
Bourland, Fred M. & Don C. Jones. (2021). Registration of two Arkot 0912 sister cotton germplasm lines. Journal of Plant Registrations. 16(1). 80–86. 1 indexed citations
12.
Hague, Steve, Jinha Jung, Akash Ashapure, et al.. (2021). Cotton row spacing and unmanned aerial vehicle sensors. Agronomy Journal. 114(1). 331–339.
13.
Ando, Atsumi, Ryan C. Kirkbride, Don C. Jones, Jane Grimwood, & Z. Jeffrey Chen. (2021). LCM and RNA-seq analyses revealed roles of cell cycle and translational regulation and homoeolog expression bias in cotton fiber cell initiation. BMC Genomics. 22(1). 309–309. 12 indexed citations
14.
Peng, Renhai, Don C. Jones, Fang Liu, & Baohong Zhang. (2020). From Sequencing to Genome Editing for Cotton Improvement. Trends in biotechnology. 39(3). 221–224. 36 indexed citations
15.
Jenkins, Johnie N., et al.. (2018). Introgression of Gossypium barbadense L. into Upland cotton germplasm RMBUP-C4S1. Euphytica. 214(7). 8 indexed citations
16.
Coneva, Viktoriya, Margaret H. Frank, John R. Tuttle, et al.. (2016). Modifications to a LATE MERISTEM IDENTITY1 gene are responsible for the major leaf shapes of Upland cotton ( Gossypium hirsutum L.). Proceedings of the National Academy of Sciences. 114(1). E57–E66. 85 indexed citations
17.
Hinze, Lori L., Élodie Gazave, Michael A. Gore, et al.. (2016). Genetic Diversity of the Two Commercial Tetraploid Cotton Species in theGossypiumDiversity Reference Set. Journal of Heredity. 107(3). 274–286. 32 indexed citations
18.
Xie, Fuliang, Don C. Jones, Qinglian Wang, Runrun Sun, & Baohong Zhang. (2015). Small RNA sequencing identifies miRNA roles in ovule and fibre development. Plant Biotechnology Journal. 13(3). 355–369. 93 indexed citations
19.
Jones, Don C.. (2014). High-Throughput Phenotyping of Drought-Adaptive Traits in Cotton. 1 indexed citations
20.
Hague, Steve, et al.. (2011). Variation in an Extra-Long Staple Upland X Medium Staple Upland Cotton F2 Population. ˜The œjournal of cotton science/Journal of cotton science. 3 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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