Mindi Zhao

748 total citations
21 papers, 390 citations indexed

About

Mindi Zhao is a scholar working on Molecular Biology, Spectroscopy and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Mindi Zhao has authored 21 papers receiving a total of 390 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 13 papers in Spectroscopy and 3 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Mindi Zhao's work include Advanced Proteomics Techniques and Applications (13 papers), Metabolomics and Mass Spectrometry Studies (10 papers) and Mass Spectrometry Techniques and Applications (7 papers). Mindi Zhao is often cited by papers focused on Advanced Proteomics Techniques and Applications (13 papers), Metabolomics and Mass Spectrometry Studies (10 papers) and Mass Spectrometry Techniques and Applications (7 papers). Mindi Zhao collaborates with scholars based in China. Mindi Zhao's co-authors include Youhe Gao, Chen Shao, Menglin Li, Zhengguang Guo, Yehong Yang, Wei Sun, Xundou Li, Ying Sun, Mingxi Li and Jianqiang Wu and has published in prestigious journals such as PLoS ONE, Scientific Reports and The FASEB Journal.

In The Last Decade

Mindi Zhao

21 papers receiving 387 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mindi Zhao China 9 211 158 45 39 36 21 390
Veronica Mainini Italy 14 209 1.0× 207 1.3× 19 0.4× 35 0.9× 62 1.7× 19 486
Gourav Bhardwaj United States 15 311 1.5× 70 0.4× 32 0.7× 125 3.2× 17 0.5× 24 537
Elvira Inglese Italy 12 242 1.1× 57 0.4× 20 0.4× 31 0.8× 48 1.3× 20 407
Juliane Hermann Germany 5 129 0.6× 60 0.4× 19 0.4× 18 0.5× 15 0.4× 12 266
Santosh D. Bhosale Finland 12 174 0.8× 73 0.5× 8 0.2× 27 0.7× 23 0.6× 20 390
Alisa Kleinhempel Germany 6 137 0.6× 99 0.6× 6 0.1× 35 0.9× 38 1.1× 8 353
Naohiko Kinoshita Japan 10 397 1.9× 49 0.3× 8 0.2× 57 1.5× 16 0.4× 26 463
Huadong Sun United States 8 104 0.5× 24 0.2× 27 0.6× 15 0.4× 21 0.6× 16 256
Henrik Lindberg Sweden 11 360 1.7× 141 0.9× 6 0.1× 104 2.7× 98 2.7× 19 591
Maciej Niedźwiecki Poland 11 76 0.4× 51 0.3× 15 0.3× 9 0.2× 36 1.0× 31 352

Countries citing papers authored by Mindi Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Mindi Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mindi Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Mindi Zhao. A scholar is included among the top collaborators of Mindi Zhao 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 Mindi Zhao. Mindi Zhao 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.
Liu, Jiaqi, Aiwei Wang, Qi Feng, et al.. (2025). Urinary metabolomics analysis based on LC-MS for the diagnosis and monitoring of acute coronary syndrome. Frontiers in Molecular Biosciences. 12. 1547476–1547476. 1 indexed citations
2.
Zhao, Mindi, et al.. (2023). Early urinary candidate biomarkers and clinical outcomes of intervention in a rat model of experimental autoimmune encephalomyelitis. Royal Society Open Science. 10(8). 230118–230118. 1 indexed citations
3.
Zhao, Mindi, Zhengguang Guo, Tao Yuan, et al.. (2022). Urinary proteomic analysis during pregnancy and its potential application in early prediction of gestational diabetes mellitus and spontaneous abortion. Annals of Translational Medicine. 10(13). 736–736. 3 indexed citations
4.
5.
Liu, Yongtao, et al.. (2020). Global chemical modifications comparison of human plasma proteome from two different age groups. Scientific Reports. 10(1). 14998–14998. 1 indexed citations
6.
Zhao, Mindi, et al.. (2020). Why are there proteins in the urine of healthy people?. Scientia Sinica Vitae. 50(3). 338–348. 1 indexed citations
7.
Shao, Chen, Mindi Zhao, Xizhao Chen, et al.. (2019). Comprehensive Analysis of Individual Variation in the Urinary Proteome Revealed Significant Gender Differences. Molecular & Cellular Proteomics. 18(6). 1110–1122. 50 indexed citations
8.
Zhao, Mindi, et al.. (2019). Evaluation of Urinary Proteome Library Generation Methods on Data‐Independent Acquisition MS Analysis and its Application in Normal Urinary Proteome Analysis. PROTEOMICS - CLINICAL APPLICATIONS. 13(5). e1800152–e1800152. 8 indexed citations
9.
Zhao, Mindi, Jianqiang Wu, Xundou Li, & Youhe Gao. (2018). Urinary candidate biomarkers in an experimental autoimmune myocarditis rat model. Journal of Proteomics. 179. 71–79. 23 indexed citations
10.
Zhao, Mindi, Yehong Yang, Zhengguang Guo, et al.. (2018). A Comparative Proteomics Analysis of Five Body Fluids: Plasma, Urine, Cerebrospinal Fluid, Amniotic Fluid, and Saliva. PROTEOMICS - CLINICAL APPLICATIONS. 12(6). e1800008–e1800008. 58 indexed citations
11.
Zhao, Mindi, Menglin Li, Yehong Yang, et al.. (2017). A comprehensive analysis and annotation of human normal urinary proteome. Scientific Reports. 7(1). 3024–3024. 121 indexed citations
12.
Wu, Jianqiang, Xundou Li, Mindi Zhao, et al.. (2017). Early Detection of Urinary Proteome Biomarkers for Effective Early Treatment of Pulmonary Fibrosis in a Rat Model. PROTEOMICS - CLINICAL APPLICATIONS. 11(11-12). 16 indexed citations
13.
Zhao, Mindi, Jianqiang Wu, & Youhe Gao. (2016). The Specific α1-Adrenergic Receptor Antagonist Prazosin Influences the Urine Proteome. PLoS ONE. 11(10). e0164796–e0164796. 2 indexed citations
14.
Zhao, Mindi, et al.. (2015). Phosphoproteins with Stability Against All Urinary Phosphatases as Potential Biomarkers in Urine. Protein and Peptide Letters. 22(9). 795–800. 5 indexed citations
15.
Zhao, Mindi, Xundou Li, Menglin Li, & Youhe Gao. (2015). Effects of anesthetics pentobarbital sodium and chloral hydrate on urine proteome. PeerJ. 3. e813–e813. 8 indexed citations
16.
Li, Menglin, Mindi Zhao, & Youhe Gao. (2015). Effect of transient blood glucose increases after oral glucose intake on the human urinary proteome. PROTEOMICS - CLINICAL APPLICATIONS. 9(5-6). 618–622. 4 indexed citations
17.
Zhao, Mindi, et al.. (2014). Changes of proteins induced by anticoagulants can be more sensitively detected in urine rather than plasma. Journal of Molecular Biomarkers & Diagnosis. 1 indexed citations
18.
Zhao, Mindi, et al.. (2014). Changes of proteins induced by anticoagulants can be more sensitively detected in urine than in plasma. Science China Life Sciences. 57(7). 649–656. 40 indexed citations
19.
Zhao, Mindi, et al.. (2014). Dynamic changes of urinary proteins in a focal segmental glomerulosclerosis rat model. Proteome Science. 12(1). 42–42. 26 indexed citations
20.
Li, Menglin, Mindi Zhao, & Youhe Gao. (2014). Changes of proteins induced by anticoagulants can be more sensitively detected in urine than in plasma (591.2). The FASEB Journal. 28(S1). 4 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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