Yanan Guo

809 total citations
23 papers, 355 citations indexed

About

Yanan Guo is a scholar working on Plant Science, Cell Biology and Molecular Biology. According to data from OpenAlex, Yanan Guo has authored 23 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Plant Science, 9 papers in Cell Biology and 8 papers in Molecular Biology. Recurrent topics in Yanan Guo's work include Plant-Microbe Interactions and Immunity (7 papers), Plant Pathogens and Fungal Diseases (7 papers) and Plant Pathogens and Resistance (4 papers). Yanan Guo is often cited by papers focused on Plant-Microbe Interactions and Immunity (7 papers), Plant Pathogens and Fungal Diseases (7 papers) and Plant Pathogens and Resistance (4 papers). Yanan Guo collaborates with scholars based in China, New Zealand and United States. Yanan Guo's co-authors include Rosie E. Bradshaw, Rebecca L. McDougal, Pranav Chettri, Carl H. Mesarich, Lukas Hunziker, Murray P. Cox, Jeffrey W. Cary, Ana M. Calvo, Sourabh Dhingra and Nari Williams and has published in prestigious journals such as Acta Materialia, Journal of Controlled Release and Molecular Ecology.

In The Last Decade

Yanan Guo

21 papers receiving 351 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yanan Guo China 11 219 118 117 47 24 23 355
Martina Celerin Canada 8 172 0.8× 90 0.8× 255 2.2× 22 0.5× 18 0.8× 12 410
Julia Kruse Germany 11 305 1.4× 220 1.9× 217 1.9× 24 0.5× 7 0.3× 33 408
Marie‐Josée Bergeron Canada 10 84 0.4× 70 0.6× 104 0.9× 48 1.0× 6 0.3× 16 222
Xi Gong China 11 166 0.8× 19 0.2× 132 1.1× 22 0.5× 47 2.0× 24 337
Klaas Schotanus United States 9 299 1.4× 107 0.9× 356 3.0× 109 2.3× 25 1.0× 12 530
Wenli Li China 13 364 1.7× 374 3.2× 121 1.0× 26 0.6× 22 0.9× 27 535
Cloe S. Pogoda United States 10 157 0.7× 47 0.4× 114 1.0× 51 1.1× 7 0.3× 21 272
S.S. Snoeijers Netherlands 8 376 1.7× 120 1.0× 237 2.0× 35 0.7× 6 0.3× 8 551
Åsa Rasmuson-Lestander Sweden 11 206 0.9× 75 0.6× 505 4.3× 24 0.5× 16 0.7× 20 711
Pádraic Corcoran Sweden 13 237 1.1× 73 0.6× 225 1.9× 12 0.3× 18 0.8× 22 431

Countries citing papers authored by Yanan Guo

Since Specialization
Citations

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

Fields of papers citing papers by Yanan Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yanan Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Yanan Guo. A scholar is included among the top collaborators of Yanan Guo 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 Yanan Guo. Yanan Guo 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.
Wu, Yao, Yanan Guo, Yifeng Jiang, et al.. (2025). Axis-selective on/off ratio amplification through bond covalency modulation in TiS3 under pressure. Acta Materialia. 299. 121487–121487.
2.
Guo, Yanan, et al.. (2025). High-Precision prediction of curling trajectory multivariate time series using the novel CasLSTM approach. PubMed. 15(1). 3468–3468. 1 indexed citations
3.
4.
Rocafort, Mercedes, Vaibhav Srivastava, Joanna K. Bowen, et al.. (2023). Cell Wall Carbohydrate Dynamics during the Differentiation of Infection Structures by the Apple Scab Fungus, Venturia inaequalis. Microbiology Spectrum. 11(3). e0421922–e0421922. 9 indexed citations
5.
Mesarich, Carl H., Irene Barnes, P.J.G.M. de Wit, et al.. (2023). Beyond the genomes of Fulvia fulva (syn. Cladosporium fulvum ) and Dothistroma septosporum : New insights into how these fungal pathogens interact with their host plants. Molecular Plant Pathology. 24(5). 474–494. 10 indexed citations
6.
Guo, Yanan, et al.. (2023). An RNA interference (RNAi) target with potential to control Dothistroma needle blight. Proceedings of the New Zealand Weed Control Conference. 76. 35–53. 2 indexed citations
7.
Wang, Lifeng, Xuepeng Sun, Yajun Peng, et al.. (2022). Genomic insights into the origin, adaptive evolution, and herbicide resistance of Leptochloa chinensis, a devastating tetraploid weedy grass in rice fields. Molecular Plant. 15(6). 1045–1058. 31 indexed citations
8.
Wang, Lu, Qianqian Liu, Rui Hao, et al.. (2022). Characterization of a Hyaluronidase-Producing Bacillus sp. CQMU-D Isolated from Soil. Current Microbiology. 79(11). 328–328. 4 indexed citations
9.
Cox, Murray P., Yanan Guo, David J. Winter, et al.. (2022). Chromosome-level assembly of the Phytophthora agathidicida genome reveals adaptation in effector gene families. Frontiers in Microbiology. 13. 1038444–1038444. 9 indexed citations
10.
11.
Wang, Lu, Qianqian Liu, Xue Gong, et al.. (2022). Cloning and Biochemical Characterization of a Hyaluronate Lyase from Bacillus sp. CQMU-D. Journal of Microbiology and Biotechnology. 33(2). 235–241. 5 indexed citations
12.
Liu, Yuchun, et al.. (2021). CHIP promotes the activation of NF-κB signaling through enhancing the K63-linked ubiquitination of TAK1. Cell Death Discovery. 7(1). 246–246. 12 indexed citations
13.
Guo, Yanan, Lukas Hunziker, Carl H. Mesarich, et al.. (2019). DsEcp2-1 is a polymorphic effector that restricts growth of Dothistroma septosporum in pine. Fungal Genetics and Biology. 135. 103300–103300. 11 indexed citations
14.
Li, Shengli, Yang Jiang, Xiaoli Liu, et al.. (2017). Telomere length is positively associated with the expression of IL-6 and MIP-1α in bone marrow mesenchymal stem cells of multiple myeloma. Molecular Medicine Reports. 16(3). 2497–2504. 9 indexed citations
15.
Bradshaw, Rosie E., Yanan Guo, M. Shahjahan Kabir, et al.. (2015). Genome‐wide gene expression dynamics of the fungal pathogen D othistroma septosporum throughout its infection cycle of the gymnosperm host P inus radiata . Molecular Plant Pathology. 17(2). 210–224. 36 indexed citations
16.
Xu, Qianghua, Xingxing Hu, Yun Liu, et al.. (2015). Evolutionary suppression of erythropoiesis via the modulation of TGF‐β signalling in an Antarctic icefish. Molecular Ecology. 24(18). 4664–4678. 31 indexed citations
17.
Mesarich, Carl H., Ioannis Stergiopoulos, Henriek G. Beenen, et al.. (2015). A conserved proline residue in Dothideomycete Avr4 effector proteins is required to trigger a Cf‐4‐dependent hypersensitive response. Molecular Plant Pathology. 17(1). 84–95. 21 indexed citations
18.
Chettri, Pranav, Ana M. Calvo, Jeffrey W. Cary, et al.. (2011). The veA gene of the pine needle pathogen Dothistroma septosporum regulates sporulation and secondary metabolism. Fungal Genetics and Biology. 49(2). 141–151. 41 indexed citations
19.
Zhang, Shuguang, Yanan Guo, & Rosie E. Bradshaw. (2010). Genetics of Dothistromin Biosynthesis in the Peanut Pathogen Passalora arachidicola. Toxins. 2(12). 2738–2753. 3 indexed citations
20.
You, Leiming, Jun Luo, Aiping Wang, et al.. (2009). A hybrid promoter-containing vector for direct cloning and enhanced expression of PCR-amplified ORFs in mammalian cells. Molecular Biology Reports. 37(6). 2757–2765. 6 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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