Ting‐Ying Wu

768 total citations
21 papers, 475 citations indexed

About

Ting‐Ying Wu is a scholar working on Molecular Biology, Plant Science and Hematology. According to data from OpenAlex, Ting‐Ying Wu has authored 21 papers receiving a total of 475 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 13 papers in Plant Science and 2 papers in Hematology. Recurrent topics in Ting‐Ying Wu's work include Plant Stress Responses and Tolerance (8 papers), Photosynthetic Processes and Mechanisms (6 papers) and Plant Gene Expression Analysis (5 papers). Ting‐Ying Wu is often cited by papers focused on Plant Stress Responses and Tolerance (8 papers), Photosynthetic Processes and Mechanisms (6 papers) and Plant Gene Expression Analysis (5 papers). Ting‐Ying Wu collaborates with scholars based in Singapore, Taiwan and Switzerland. Ting‐Ying Wu's co-authors include Wilhelm Gruissem, Navreet K. Bhullar, Daisuke Urano, Yee‐yung Charng, Raymond W.M. Fung, Ming‐Jung Liu, Christina B. Azodi, Alan M. Jones, Takayuki Tohge and Boris Szurek and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Plant Cell and PLANT PHYSIOLOGY.

In The Last Decade

Ting‐Ying Wu

20 papers receiving 472 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ting‐Ying Wu Singapore 12 400 205 43 31 21 21 475
Mara Schuler Germany 7 568 1.4× 156 0.8× 26 0.6× 23 0.7× 11 0.5× 8 627
Marco Klatte Germany 7 735 1.8× 315 1.5× 21 0.5× 22 0.7× 18 0.9× 9 795
Narayanan N. Narayanan United States 16 617 1.5× 117 0.6× 49 1.1× 25 0.8× 47 2.2× 17 686
Hong-Qing Ling China 11 1.1k 2.9× 221 1.1× 43 1.0× 38 1.2× 31 1.5× 12 1.2k
Guilherme Leitão Duarte Brazil 8 503 1.3× 146 0.7× 27 0.6× 41 1.3× 20 1.0× 14 555
Julien Bonneau Australia 13 467 1.2× 95 0.5× 60 1.4× 47 1.5× 67 3.2× 16 519
H. Bäumlein Germany 11 398 1.0× 141 0.7× 31 0.7× 14 0.5× 19 0.9× 14 489
Chengjin Guo China 16 660 1.6× 201 1.0× 17 0.4× 18 0.6× 17 0.8× 48 705
Sultana Rasheed Japan 7 325 0.8× 105 0.5× 21 0.5× 14 0.5× 11 0.5× 11 366
Giulio Catarcione Italy 8 278 0.7× 104 0.5× 16 0.4× 30 1.0× 17 0.8× 10 315

Countries citing papers authored by Ting‐Ying Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ting‐Ying Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ting‐Ying Wu. 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 Ting‐Ying Wu. The network helps show where Ting‐Ying Wu may publish in the future.

Co-authorship network of co-authors of Ting‐Ying Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Ting‐Ying Wu. A scholar is included among the top collaborators of Ting‐Ying Wu 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 Ting‐Ying Wu. Ting‐Ying Wu 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.
Yen, Ming‐Ren, Yaru Li, Chia‐Yi Cheng, Ting‐Ying Wu, & Ming‐Jung Liu. (2025). TISCalling: leveraging machine learning to identify translational initiation sites in plants and viruses. Plant Molecular Biology. 115(4). 102–102.
2.
Wu, Ting‐Ying, et al.. (2024). Modeling alternative translation initiation sites in plants reveals evolutionarily conserved cis -regulatory codes in eukaryotes. Genome Research. 34(2). 272–285. 4 indexed citations
3.
Dong, Yating, et al.. (2024). Hyperspectral imaging of liverwort Marchantia polymorpha identifies MpWRKY10 as a key regulator defining Foliar pigmentation patterns. Cell Reports. 43(7). 114463–114463. 4 indexed citations
4.
Dong, Yating, Ting‐Ying Wu, & Daisuke Urano. (2023). Heterotrimeric G proteins in crop improvement. Molecular Plant. 16(5). 806–808. 1 indexed citations
5.
Wu, Ting‐Ying, et al.. (2022). G protein signaling and metabolic pathways as evolutionarily conserved mechanisms to combat calcium deficiency. New Phytologist. 237(2). 615–630. 7 indexed citations
6.
Wu, Ting‐Ying, et al.. (2022). Diversification of heat shock transcription factors expanded thermal stress responses during early plant evolution. The Plant Cell. 34(10). 3557–3576. 24 indexed citations
7.
Wu, Ting‐Ying, et al.. (2022). G protein controls stress readiness by modulating transcriptional and metabolic homeostasis in Arabidopsis thaliana and Marchantia polymorpha. Molecular Plant. 15(12). 1889–1907. 15 indexed citations
8.
Wu, Ting‐Ying, et al.. (2022). Interplay between ARABIDOPSIS Gβ and WRKY transcription factors differentiates environmental stress responses. PLANT PHYSIOLOGY. 190(1). 813–827. 9 indexed citations
9.
Wu, Ting‐Ying, et al.. (2021). Evolutionarily conserved hierarchical gene regulatory networks for plant salt stress response. Nature Plants. 7(6). 787–799. 69 indexed citations
10.
Wu, Ting‐Ying, et al.. (2020). Genome Wide Analysis of the Transcriptional Profiles in Different Regions of the Developing Rice Grains. Rice. 13(1). 62–62. 15 indexed citations
11.
Wu, Ting‐Ying, Takayuki Tohge, Alisdair R. Fernie, et al.. (2019). Enhancement of vitamin B6 levels in rice expressing Arabidopsis vitamin B6 biosynthesis de novo genes. The Plant Journal. 99(6). 1047–1065. 34 indexed citations
12.
Urano, Daisuke, et al.. (2019). Quantitative morphological phenomics of rice G protein mutants portend autoimmunity. Developmental Biology. 457(1). 83–90. 14 indexed citations
13.
Wu, Ting‐Ying, et al.. (2018). Comparative leaf proteomic profiling of salt-treated natural variants of Imperata cylindrica. SHILAP Revista de lepidopterología. 1 indexed citations
14.
Wu, Ting‐Ying & Daisuke Urano. (2018). Genetic and Systematic Approaches Toward G Protein-Coupled Abiotic Stress Signaling in Plants. Frontiers in Plant Science. 9. 1378–1378. 15 indexed citations
15.
Wu, Ting‐Ying, Wilhelm Gruissem, & Navreet K. Bhullar. (2018). Facilitated citrate-dependent iron translocation increases rice endosperm iron and zinc concentrations. Plant Science. 270. 13–22. 34 indexed citations
16.
Wu, Ting‐Ying, et al.. (2018). The association between early treatment with amantadine and delayed onset of levodopa-induced dyskinesia in patients with Parkinson’s disease. Parkinsonism & Related Disorders. 46. e14–e15. 1 indexed citations
17.
Wu, Ting‐Ying, Wilhelm Gruissem, & Navreet K. Bhullar. (2018). Targeting intracellular transport combined with efficient uptake and storage significantly increases grain iron and zinc levels in rice. Plant Biotechnology Journal. 17(1). 9–20. 51 indexed citations
18.
19.
Wu, Ting‐Ying, et al.. (2017). Enhanced grain iron levels in iron-regulated metal transporter, nicotianamine synthase, and ferritin gene cassette. Frontiers in Plant Science. 8. 130. 4 indexed citations
20.
Wu, Ting‐Ying, et al.. (2013). Interplay between Heat Shock Proteins HSP101 and HSA32 Prolongs Heat Acclimation Memory Posttranscriptionally in Arabidopsis  . PLANT PHYSIOLOGY. 161(4). 2075–2084. 91 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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