Tom Hsiang

8.7k total citations · 1 hit paper
346 papers, 6.2k citations indexed

About

Tom Hsiang is a scholar working on Plant Science, Cell Biology and Molecular Biology. According to data from OpenAlex, Tom Hsiang has authored 346 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 253 papers in Plant Science, 190 papers in Cell Biology and 121 papers in Molecular Biology. Recurrent topics in Tom Hsiang's work include Plant Pathogens and Fungal Diseases (189 papers), Plant-Microbe Interactions and Immunity (76 papers) and Plant Disease Resistance and Genetics (67 papers). Tom Hsiang is often cited by papers focused on Plant Pathogens and Fungal Diseases (189 papers), Plant-Microbe Interactions and Immunity (76 papers) and Plant Disease Resistance and Genetics (67 papers). Tom Hsiang collaborates with scholars based in Canada, China and United States. Tom Hsiang's co-authors include Paul H. Goodwin, Junbin Huang, Lu Zheng, John H. Sheesley, Genichi Taguchi, Qili Li, Guoqing Li, Ping Ning, Dàohóng Jiāng and Lin Yang and has published in prestigious journals such as Journal of Biological Chemistry, Angewandte Chemie International Edition and PLoS ONE.

In The Last Decade

Tom Hsiang

319 papers receiving 5.9k citations

Hit Papers

Quality Engineering in Production Systems 1990 2026 2002 2014 1990 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Quality Engineering in Production Systems
    1990 673 citations Tom Hsiang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Hsiang Canada 39 4.2k 2.4k 1.8k 607 557 346 6.2k
Geert Haesaert Belgium 40 4.3k 1.0× 1.1k 0.5× 608 0.3× 698 1.1× 97 0.2× 219 5.6k
J. H. Graham United States 42 4.0k 0.9× 886 0.4× 504 0.3× 229 0.4× 427 0.8× 113 5.1k
Serge Savary France 35 5.5k 1.3× 955 0.4× 954 0.5× 779 1.3× 218 0.4× 126 7.0k
Robert Dietrich United States 32 5.7k 1.4× 622 0.3× 2.5k 1.4× 355 0.6× 105 0.2× 66 6.8k
Yanbin Yin United States 39 2.6k 0.6× 563 0.2× 4.3k 2.4× 306 0.5× 398 0.7× 123 7.8k
Stephan Waack Germany 17 2.2k 0.5× 650 0.3× 3.3k 1.9× 547 0.9× 350 0.6× 47 5.6k
Ranajit Bandyopadhyay Nigeria 46 5.6k 1.4× 1.9k 0.8× 637 0.4× 515 0.8× 98 0.2× 199 6.4k
Edward E. Schilling United States 28 2.7k 0.6× 508 0.2× 2.9k 1.6× 3.1k 5.2× 124 0.2× 109 6.4k
Qing Yao China 31 2.0k 0.5× 203 0.1× 652 0.4× 157 0.3× 348 0.6× 179 3.2k
Xiangming Xu United Kingdom 41 5.8k 1.4× 2.8k 1.2× 905 0.5× 1.2k 2.0× 94 0.2× 264 6.9k

Countries citing papers authored by Tom Hsiang

Since Specialization
Citations

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

Fields of papers citing papers by Tom Hsiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom Hsiang. 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 Tom Hsiang. The network helps show where Tom Hsiang may publish in the future.

Co-authorship network of co-authors of Tom Hsiang

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Hsiang. A scholar is included among the top collaborators of Tom Hsiang 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 Tom Hsiang. Tom Hsiang 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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Sohail, Muhammad Aamir, Yiqian Zhang, Zhao Wang, et al.. (2025). Pan-genome analysis of Ralstonia pseudosolanacearum associated with tobacco bacterial wilt in China. BMC Microbiology. 25(1). 775–775.
3.
Tang, Lihua, et al.. (2024). Dimethyl trisulfide reduces postharvest anthracnose and enhances mango quality, and a potential molecular mechanism against Colletotrichum gloeosporioides. Pesticide Biochemistry and Physiology. 206. 106174–106174. 3 indexed citations
4.
Wang, Xinye, Bin Zhu, Guoliang Zhu, et al.. (2024). Identifying sesterterpenoids via feature-based molecular networking and small-scale fermentation. Applied Microbiology and Biotechnology. 108(1). 483–483.
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Zhu, Yan, Chao Wang, Shurui Zhang, et al.. (2024). Yield increment and transcriptome response caused by blue light treatment in Hericium coralloides. BMC Genomics. 25(1). 1244–1244.
6.
Zhang, Yi, Hancheng Wang, Xinghong Zhang, et al.. (2024). Response of microbial communities in the tobacco phyllosphere under the stress of validamycin. Frontiers in Microbiology. 14. 1328179–1328179. 5 indexed citations
7.
Wang, Lili, Hong Hu, Xiaolan Zhou, et al.. (2024). S-palmitoylation of MAP kinase is essential for fungal virulence. mBio. 15(12). e0270424–e0270424.
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Huang, Rong, Jingyi Ren, Lihua Tang, et al.. (2023). The evolution of mini-chromosomes in the fungal genus Colletotrichum. mBio. 14(4). e0062923–e0062923. 12 indexed citations
11.
You-Wei, Du, Xiaofei Liang, Bo Wang, et al.. (2023). Sufficient coumarin accumulation improves apple resistance toCytospora maliunder high-potassium status. PLANT PHYSIOLOGY. 192(2). 1396–1419. 23 indexed citations
12.
Malewski, Tadeusz, et al.. (2022). Use of Secondary Metabolites of Wood-Decaying Fungi to Reduce Damping off Disease. Forests. 13(8). 1208–1208. 8 indexed citations
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Oszako, Tomasz, С. Бакиер, Lassaâd Belbahri, et al.. (2021). Dothistroma septosporum Not Detected in Pinus sylvestris Seed Trees from Investigated Stands in Southern Poland. Forests. 12(10). 1323–1323. 1 indexed citations
15.
Lefort, François, Monika Asztemborska, Rafał Szmigielski, et al.. (2020). Detection of Fungi and Oomycetes by Volatiles Using E-Nose and SPME-GC/MS Platforms. Molecules. 25(23). 5749–5749. 43 indexed citations
16.
Nowakowska, Justyna A., et al.. (2020). Interactions between Phytophthora cactorum, Armillaria gallica and Betula pendula Roth. Seedlings Subjected to Defoliation. Forests. 11(10). 1107–1107. 15 indexed citations
17.
Zheng, Lu, Shibo Fang, & Tom Hsiang. (2013). Genetic structure of a population of Rhizoctonia solani AG 2-2 IIIB from Agrostis stolonifera revealed by inter-simple sequence repeat (ISSR) markers. Canadian Journal of Plant Pathology. 35(4). 476–481. 6 indexed citations
18.
Zheng, Lu, et al.. (2010). Integrated control of garlic leaf blight caused by Stemphylium solani in China. Canadian Journal of Plant Pathology. 32(2). 135–145. 9 indexed citations
19.
Hsiang, Tom, et al.. (2007). Sporulation and Identity of Tar Spot of Maple in Canada. Acta silvatica & lignaria Hungarica. 3(Special Edition). 71–74. 2 indexed citations
20.
Hsiang, Tom, et al.. (1998). Low level of DNA polymorphisms in isolates of Leptosphaeria korrae pathogenic on Poa pratensis. Canadian Journal of Plant Pathology. 20(1). 48–54. 9 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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