Jonathan D. Neubauer

520 total citations
17 papers, 394 citations indexed

About

Jonathan D. Neubauer is a scholar working on Plant Science, Cell Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Jonathan D. Neubauer has authored 17 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Plant Science, 9 papers in Cell Biology and 3 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Jonathan D. Neubauer's work include Plant Pathogens and Fungal Diseases (9 papers), Plant Disease Management Techniques (5 papers) and Plant Disease Resistance and Genetics (5 papers). Jonathan D. Neubauer is often cited by papers focused on Plant Pathogens and Fungal Diseases (9 papers), Plant Disease Management Techniques (5 papers) and Plant Disease Resistance and Genetics (5 papers). Jonathan D. Neubauer collaborates with scholars based in United States, Netherlands and United Kingdom. Jonathan D. Neubauer's co-authors include Edward C. Lulai, Jeffrey C. Suttle, Melvin D. Bolton, Asunta L. Thompson, Gary A. Secor, Rebecca Spanner, Ronnie de Jonge, L. G. Campbell, Malaika K. Ebert and Bart P. H. J. Thomma and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Phytopathology and Postharvest Biology and Technology.

In The Last Decade

Jonathan D. Neubauer

17 papers receiving 385 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan D. Neubauer United States 12 349 145 84 45 37 17 394
Xianhui Yin China 11 251 0.7× 151 1.0× 81 1.0× 45 1.0× 46 1.2× 27 322
Shun Feng China 11 401 1.1× 130 0.9× 96 1.1× 38 0.8× 53 1.4× 21 454
Kyungseok Park South Korea 13 480 1.4× 107 0.7× 180 2.1× 24 0.5× 24 0.6× 27 567
Byeong-Jin Cha South Korea 9 321 0.9× 111 0.8× 56 0.7× 51 1.1× 65 1.8× 14 377
Guangzheng Sun China 10 237 0.7× 93 0.6× 112 1.3× 39 0.9× 23 0.6× 21 307
Camilla Martini Italy 5 294 0.8× 192 1.3× 65 0.8× 69 1.5× 78 2.1× 6 337
Rania Aydi Ben Abdallah Tunisia 13 426 1.2× 222 1.5× 81 1.0× 17 0.4× 48 1.3× 42 485
Malaika K. Ebert United States 9 320 0.9× 168 1.2× 99 1.2× 68 1.5× 19 0.5× 12 389
D. Nirmala Devi India 4 223 0.6× 171 1.2× 61 0.7× 22 0.5× 37 1.0× 8 311
A. Gotor-Vila Spain 9 277 0.8× 115 0.8× 65 0.8× 41 0.9× 57 1.5× 9 323

Countries citing papers authored by Jonathan D. Neubauer

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan D. Neubauer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan D. Neubauer

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

All Works

17 of 17 papers shown
1.
Mendoza, Luis E. del Río, Aiming Qi, Dilip K. Lakshman, et al.. (2023). Resistance to QoI and DMI Fungicides Does Not Reduce Virulence of C. beticola Isolates in North Central United States. Plant Disease. 107(9). 2825–2829. 2 indexed citations
2.
Spanner, Rebecca, Jonathan K. Richards, Viviana Rivera-Varas, et al.. (2021). Genome-Wide Association and Selective Sweep Studies Reveal the Complex Genetic Architecture of DMI Fungicide Resistance in Cercospora beticola. Genome Biology and Evolution. 13(9). 21 indexed citations
3.
Spanner, Rebecca, Jonathan D. Neubauer, Thies Marten Heick, et al.. (2021). SeedborneCercospora beticolaCan Initiate Cercospora Leaf Spot from Sugar Beet (Beta vulgaris) Fruit Tissue. Phytopathology. 112(5). 1016–1028. 11 indexed citations
4.
Neubauer, Jonathan D., et al.. (2020). Rapid Detection of Cercospora beticola in Sugar Beet and Mutations Associated with Fungicide Resistance Using LAMP or Probe-Based qPCR. Plant Disease. 104(6). 1654–1661. 21 indexed citations
5.
Ebert, Malaika K., Lorena I. Rangel, Rebecca Spanner, et al.. (2020). Identification and characterization of Cercospora beticola necrosis‐inducing effector CbNip1. Molecular Plant Pathology. 22(3). 301–316. 16 indexed citations
6.
Lulai, Edward C., et al.. (2019). Inhibitors of tri- and tetra- polyamine oxidation, but not diamine oxidation, impair the initial stages of wound-induced suberization. Journal of Plant Physiology. 246-247. 153092–153092. 1 indexed citations
7.
Weiland, John J., et al.. (2019). Prevalence and Distribution of Beet Necrotic Yellow Vein Virus Strains in North Dakota and Minnesota. Plant Disease. 103(8). 2083–2089. 12 indexed citations
8.
Jonge, Ronnie de, Malaika K. Ebert, Jeffrey C. Suttle, et al.. (2018). Gene cluster conservation provides insight into cercosporin biosynthesis and extends production to the genus Colletotrichum. Proceedings of the National Academy of Sciences. 115(24). E5459–E5466. 67 indexed citations
9.
Lulai, Edward C., et al.. (2015). Wounding induces changes in cytokinin and auxin content in potato tuber, but does not induce formation of gibberellins. Journal of Plant Physiology. 191. 22–28. 22 indexed citations
10.
11.
Lulai, Edward C., Jonathan D. Neubauer, & Jeffrey C. Suttle. (2014). Kinetics and localization of wound-induced DNA biosynthesis in potato tuber. Journal of Plant Physiology. 171(17). 1571–1575. 8 indexed citations
12.
Lulai, Edward C., et al.. (2014). The Pink Eye Syndrome Does Not Impair Tuber Fresh Cut Wound-Related Responses. American Journal of Potato Research. 91(5). 467–475. 1 indexed citations
13.
Lulai, Edward C. & Jonathan D. Neubauer. (2014). Wound-induced suberization genes are differentially expressed, spatially and temporally, during closing layer and wound periderm formation. Postharvest Biology and Technology. 90. 24–33. 75 indexed citations
14.
Suttle, Jeffrey C., et al.. (2013). Wounding of potato tubers induces increases in ABA biosynthesis and catabolism and alters expression of ABA metabolic genes. Journal of Plant Physiology. 170(6). 560–566. 30 indexed citations
15.
Neubauer, Jonathan D., Edward C. Lulai, Asunta L. Thompson, Jeffrey C. Suttle, & Melvin D. Bolton. (2012). Wounding coordinately induces cell wall protein, cell cycle and pectin methyl esterase genes involved in tuber closing layer and wound periderm development. Journal of Plant Physiology. 169(6). 586–595. 37 indexed citations
16.
Neubauer, Jonathan D., Edward C. Lulai, Asunta L. Thompson, et al.. (2012). Molecular and cytological aspects of native periderm maturation in potato tubers. Journal of Plant Physiology. 170(4). 413–423. 20 indexed citations
17.
Lulai, Edward C., et al.. (2011). Coordinate expression of AOS genes and JA accumulation: JA is not required for initiation of closing layer in wound healing tubers. Journal of Plant Physiology. 168(9). 976–982. 32 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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