Huiru Tang

17.7k total citations
263 papers, 10.4k citations indexed

About

Huiru Tang is a scholar working on Molecular Biology, Physiology and Spectroscopy. According to data from OpenAlex, Huiru Tang has authored 263 papers receiving a total of 10.4k indexed citations (citations by other indexed papers that have themselves been cited), including 137 papers in Molecular Biology, 42 papers in Physiology and 41 papers in Spectroscopy. Recurrent topics in Huiru Tang's work include Metabolomics and Mass Spectrometry Studies (98 papers), Diet and metabolism studies (25 papers) and NMR spectroscopy and applications (22 papers). Huiru Tang is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (98 papers), Diet and metabolism studies (25 papers) and NMR spectroscopy and applications (22 papers). Huiru Tang collaborates with scholars based in China, United Kingdom and United States. Huiru Tang's co-authors include Yulan Wang, Fuhua Hao, Jeremy K. Nicholson, John C. Lindon, Yanpeng An, Elaine Holmes, Peter Belton, Limin Zhang, Chaoni Xiao and B.P. Hills and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Huiru Tang

254 papers receiving 10.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Huiru Tang China 60 5.6k 1.4k 1.4k 837 815 263 10.4k
Yulan Wang China 71 9.9k 1.8× 2.5k 1.8× 924 0.7× 1.4k 1.6× 1.1k 1.3× 429 17.2k
Lixia Chen China 49 4.8k 0.9× 468 0.3× 1.2k 0.9× 733 0.9× 856 1.1× 506 11.7k
Haider Raza United Arab Emirates 38 6.9k 1.2× 1.2k 0.9× 1.8k 1.3× 840 1.0× 521 0.6× 114 13.4k
Takaaki Akaike Japan 71 7.5k 1.3× 3.2k 2.3× 820 0.6× 1.6k 1.9× 1.2k 1.4× 325 17.5k
Peter J. O’Brien Canada 78 8.3k 1.5× 1.9k 1.4× 1.6k 1.1× 1.2k 1.4× 1.3k 1.6× 403 22.4k
Andrea Scaloni Italy 63 7.4k 1.3× 865 0.6× 2.6k 1.9× 450 0.5× 533 0.7× 403 13.5k
Yitao Wang Macao 62 6.7k 1.2× 486 0.4× 2.1k 1.5× 1.0k 1.2× 990 1.2× 359 14.2k
Haiping Hao China 60 6.7k 1.2× 978 0.7× 905 0.7× 1.5k 1.8× 929 1.1× 365 12.5k
Jie Zhang China 52 6.6k 1.2× 816 0.6× 1.2k 0.9× 640 0.8× 687 0.8× 484 12.2k
Danyelle M. Townsend United States 50 6.3k 1.1× 754 0.5× 673 0.5× 519 0.6× 740 0.9× 160 12.2k

Countries citing papers authored by Huiru Tang

Since Specialization
Citations

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

Fields of papers citing papers by Huiru Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huiru Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Huiru Tang. A scholar is included among the top collaborators of Huiru Tang 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 Huiru Tang. Huiru Tang 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.
Tang, Huiru, et al.. (2025). Salivary effector SfPDI modulates plant defense responses to enhance foraging efficiency of Spodoptera frugiperda. International Journal of Biological Macromolecules. 308(Pt 2). 142548–142548.
2.
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Xia, Mingfeng, Yuxiang Dai, Qingxia Huang, et al.. (2025). Cross-ancestry analyses of Chinese and European populations reveal insights into the genetic architecture and disease implication of metabolites. Cell Genomics. 5(4). 100810–100810. 2 indexed citations
4.
5.
Huang, Qingxia, Xiaoxuan Yi, Huan Wang, et al.. (2024). Reproducibility of the NMR-based quantitative metabolomics and HBV-caused changes in human serum lipoprotein subclasses and small metabolites. Journal of Pharmaceutical Analysis. 15(7). 101180–101180. 3 indexed citations
6.
Mei, Zhendong, Lili Xu, Qingxia Huang, et al.. (2024). Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering Therapy. Journal of the American Heart Association. 13(24). e036906–e036906. 4 indexed citations
7.
Huang, Qingxia, S. U. Qadri, Hua Bian, et al.. (2024). A metabolome-derived score predicts metabolic dysfunction-associated steatohepatitis and mortality from liver disease. Journal of Hepatology. 82(5). 781–793. 7 indexed citations
8.
Lu, Qi, Junxiang Chen, Limiao Jiang, et al.. (2023). Gut microbiota-derived secondary bile acids, bile acids receptor polymorphisms, and risk of cardiovascular disease in individuals with newly diagnosed type 2 diabetes: a cohort study. American Journal of Clinical Nutrition. 119(2). 324–332. 20 indexed citations
9.
Li, Jialin, Qingxia Huang, Yingzhe Wang, et al.. (2023). Circulating Lipoproteins Mediate the Association Between Cardiovascular Risk Factors and Cognitive Decline: A Community-Based Cohort Study. PubMed. 4(1). 51–55. 7 indexed citations
10.
Chen, Zhangwei, Danbo Lu, Yuan Wu, et al.. (2023). Quantitative Profiling of Serum Carnitines Facilitates the Etiology Diagnosis and Prognosis Prediction in Heart Failure. Molecules. 28(14). 5345–5345. 5 indexed citations
11.
Sun, Yuting, et al.. (2023). Reliable quantification of citrate isomers and isobars with direct-infusion tandem mass spectrometry. Talanta. 259. 124477–124477. 9 indexed citations
12.
Zheng, Jiao, Yunqin Chen, Jibin Dong, et al.. (2021). Inducible phospholipid transfer protein deficiency ameliorates atherosclerosis. Atherosclerosis. 324. 9–17. 8 indexed citations
13.
14.
Sun, Yuting, Huiru Tang, & Yulan Wang. (2021). Progress and Challenges in Quantifying Carbonyl-Metabolomic Phenomes with LC-MS/MS. Molecules. 26(20). 6147–6147. 18 indexed citations
15.
Song, Jiangping, Liang Chen, Xiao Chen, et al.. (2020). Elevated plasma β-hydroxybutyrate predicts adverse outcomes and disease progression in patients with arrhythmogenic cardiomyopathy. Science Translational Medicine. 12(530). 64 indexed citations
16.
Wu, Xiangyu, et al.. (2020). Quantitative Metabonomic Analysis Reveals the Germination-Associated Dynamic and Systemic Biochemical Changes for Mung-Bean (Vigna radiata) Seeds. Journal of Proteome Research. 19(6). 2457–2470. 7 indexed citations
17.
Zhang, Limin, et al.. (2017). Colon Ascendens Stent Peritonitis (CASP) Induces Excessive Inflammation and Systemic Metabolic Dysfunction in a Septic Rat Model. Journal of Proteome Research. 17(1). 680–688. 6 indexed citations
18.
Wan, Qianfen, et al.. (2015). The toxicity of acute exposure to T-2 toxin evaluated by the metabonomics technique. Molecular BioSystems. 11(3). 882–891. 36 indexed citations
19.
Jiang, Limiao, Xiu‐Ju Zhao, Chongyang Huang, et al.. (2014). Dynamic changes in metabolic profiles of rats subchronically exposed to mequindox. Molecular BioSystems. 10(11). 2914–2922. 8 indexed citations
20.
He, Q., Pingping Ren, Xiangfeng Kong, et al.. (2011). Intrauterine growth restriction alters the metabonome of the serum and jejunum in piglets. Molecular BioSystems. 7(7). 2147–2155. 64 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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