Si Wu

3.1k total citations · 1 hit paper
32 papers, 829 citations indexed

About

Si Wu is a scholar working on Molecular Biology, Physiology and Genetics. According to data from OpenAlex, Si Wu has authored 32 papers receiving a total of 829 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 6 papers in Physiology and 5 papers in Genetics. Recurrent topics in Si Wu's work include Metabolomics and Mass Spectrometry Studies (14 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and Nutrition and Health in Aging (4 papers). Si Wu is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (14 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and Nutrition and Health in Aging (4 papers). Si Wu collaborates with scholars based in China, United States and Germany. Si Wu's co-authors include Xin Dong, Guangguo Tan, Yifeng Chai, Yariv Brotman, Alisdair R. Fernie, M Snyder, Zhenyu Zhu, Lothar Willmitzer, Wuhong Li and Álvaro Cuadros‐Inostroza and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Si Wu

29 papers receiving 818 citations

Hit Papers

Dynamic lipidome alterations associated with human health... 2023 2026 2024 2025 2023 25 50 75 100
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. Dynamic lipidome alterations associated with human health, disease and ageing
    2023 111 citations Daniel Hornburg, Si Wu et al. Nature Metabolism profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Si Wu China 16 463 197 122 90 76 32 829
Ping‐Ting Xiao China 11 393 0.8× 126 0.6× 102 0.8× 23 0.3× 93 1.2× 18 701
Xiaoyan Pang China 18 382 0.8× 98 0.5× 50 0.4× 71 0.8× 224 2.9× 35 883
Franco Ferrari Italy 18 505 1.1× 194 1.0× 86 0.7× 23 0.3× 91 1.2× 39 931
Ling Xiao China 15 443 1.0× 212 1.1× 122 1.0× 22 0.2× 122 1.6× 42 842
Sylvia J. Wowro Germany 11 519 1.1× 96 0.5× 52 0.4× 73 0.8× 35 0.5× 24 814
Nan Si China 19 523 1.1× 128 0.6× 78 0.6× 31 0.3× 161 2.1× 56 890
Fangbo Xia China 15 293 0.6× 121 0.6× 44 0.4× 22 0.2× 73 1.0× 25 582
Min Ho South Korea 17 537 1.2× 45 0.2× 169 1.4× 83 0.9× 86 1.1× 59 977
Shuisheng Wu China 14 421 0.9× 84 0.4× 86 0.7× 24 0.3× 147 1.9× 31 646
Limei Shan China 17 497 1.1× 121 0.6× 111 0.9× 33 0.4× 235 3.1× 24 1.1k

Countries citing papers authored by Si Wu

Since Specialization
Citations

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

Fields of papers citing papers by Si Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Si Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Si Wu. A scholar is included among the top collaborators of Si 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 Si Wu. Si 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.
Wu, Si, Youjun Zhang, Lei Yang, et al.. (2025). The homeostasis of β‐alanine is key for Arabidopsis reproductive growth and development. The Plant Journal. 122(1). e70134–e70134.
2.
Hu, Lei, et al.. (2025). GaN-based blue laser diodes with output power of 5 W and lifetime over 20 000 h aged at 60 °C. Journal of Semiconductors. 46(4). 40501–40501.
3.
Fu, Wentao, Xiaobao Yang, Si Wu, et al.. (2025). High-dose vitamin C: A promising anti-tumor agent, insight from mechanisms, clinical research, and challenges. Genes & Diseases. 13(2). 101742–101742. 1 indexed citations
4.
Hornburg, Daniel, Si Wu, Mahdi Moqri, et al.. (2023). Dynamic lipidome alterations associated with human health, disease and ageing. Nature Metabolism. 5(9). 1578–1594. 111 indexed citations breakdown →
5.
6.
7.
Metwally, Ahmed A., Si Wu, Ryan Kellogg, et al.. (2022). Robust identification of temporal biomarkers in longitudinal omics studies. Bioinformatics. 38(15). 3802–3811. 11 indexed citations
8.
Yang, Jingzhi, et al.. (2022). New Function of Cholesterol Oxidation Products Involved in Osteoporosis Pathogenesis. International Journal of Molecular Sciences. 23(4). 2020–2020. 15 indexed citations
9.
Shen, Xiaotao, Si Wu, Liang Liang, et al.. (2021). metID: an R package for automatable compound annotation for LC−MS-based data. Bioinformatics. 38(2). 568–569. 29 indexed citations
10.
Wu, Si, Dijun Chen, & M Snyder. (2021). Network biology bridges the gaps between quantitative genetics and multi-omics to map complex diseases. Current Opinion in Chemical Biology. 66. 102101–102101. 18 indexed citations
11.
Zhang, Fei, Jinfeng Wu, Nir Sade, et al.. (2021). Genomic basis underlying the metabolome-mediated drought adaptation of maize. Genome biology. 22(1). 260–260. 73 indexed citations
12.
Zhang, Qunfeng, Si Wu, Yan Li, et al.. (2018). Characterization of three different classes of non-fermented teas using untargeted metabolomics. Food Research International. 121. 697–704. 30 indexed citations
13.
Alseekh, Saleh, Si Wu, Yariv Brotman, & Alisdair R. Fernie. (2018). Guidelines for Sample Normalization to Minimize Batch Variation for Large-Scale Metabolic Profiling of Plant Natural Genetic Variance. Methods in molecular biology. 1778. 33–46. 11 indexed citations
14.
Wu, Si, Takayuki Tohge, Álvaro Cuadros‐Inostroza, et al.. (2017). Mapping the Arabidopsis Metabolic Landscape by Untargeted Metabolomics at Different Environmental Conditions. Molecular Plant. 11(1). 118–134. 100 indexed citations
15.
Wu, Si, Saleh Alseekh, Álvaro Cuadros‐Inostroza, et al.. (2016). Combined Use of Genome-Wide Association Data and Correlation Networks Unravels Key Regulators of Primary Metabolism in Arabidopsis thaliana. PLoS Genetics. 12(10). e1006363–e1006363. 59 indexed citations
16.
17.
Wu, Si, Si Chen, Xin Dong, et al.. (2014). Lipidomic profiling reveals significant alterations in lipid biochemistry in hypothyroid rat cerebellum and the therapeutic effects of Sini decoction. Journal of Ethnopharmacology. 159. 262–273. 16 indexed citations
18.
Wu, Si, Guangguo Tan, Xin Dong, et al.. (2013). Metabolic Profiling Provides a System Understanding of Hypothyroidism in Rats and Its Application. PLoS ONE. 8(2). e55599–e55599. 41 indexed citations
19.
Wu, Si, Yue Gao, Xin Dong, et al.. (2012). Serum metabonomics coupled with Ingenuity Pathway Analysis characterizes metabolic perturbations in response to hypothyroidism induced by propylthiouracil in rats. Journal of Pharmaceutical and Biomedical Analysis. 72. 109–114. 21 indexed citations
20.
Gao, Peng, Ruiyan Fu, Dawei Yang, et al.. (2009). Optimization of a GC–MS metabolic fingerprint method and its application in characterizing engineered bacterial metabolic shift. Journal of Separation Science. 32(13). 2281–2288. 11 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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