Shanlei Qiao

1.1k total citations
28 papers, 857 citations indexed

About

Shanlei Qiao is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis and Physiology. According to data from OpenAlex, Shanlei Qiao has authored 28 papers receiving a total of 857 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Health, Toxicology and Mutagenesis and 3 papers in Physiology. Recurrent topics in Shanlei Qiao's work include Effects and risks of endocrine disrupting chemicals (6 papers), Metabolomics and Mass Spectrometry Studies (5 papers) and Toxic Organic Pollutants Impact (5 papers). Shanlei Qiao is often cited by papers focused on Effects and risks of endocrine disrupting chemicals (6 papers), Metabolomics and Mass Spectrometry Studies (5 papers) and Toxic Organic Pollutants Impact (5 papers). Shanlei Qiao collaborates with scholars based in China, United States and South Korea. Shanlei Qiao's co-authors include Yankai Xia, Xinru Wang, Minjian Chen, Wei Jia, Pengfei Zhu, Bin Xu, Rong Tang, Xiaojiao Chen, Shoulin Wang and Chuncheng Lu and has published in prestigious journals such as PLoS ONE, The Science of The Total Environment and Journal of Hazardous Materials.

In The Last Decade

Shanlei Qiao

27 papers receiving 841 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shanlei Qiao China 14 322 301 127 118 86 28 857
Changhwan Ahn South Korea 19 261 0.8× 303 1.0× 103 0.8× 46 0.4× 73 0.8× 75 1.0k
Reza J. Rasoulpour United States 19 218 0.7× 560 1.9× 88 0.7× 89 0.8× 72 0.8× 45 1.2k
Sarbani Giri India 19 297 0.9× 266 0.9× 46 0.4× 49 0.4× 57 0.7× 58 1.2k
Persefoni Fragkiadaki Greece 21 127 0.4× 352 1.2× 379 3.0× 44 0.4× 95 1.1× 49 1.2k
Boris Ročić Croatia 12 284 0.9× 103 0.3× 66 0.5× 181 1.5× 88 1.0× 35 732
Yuqin Shi China 20 392 1.2× 420 1.4× 48 0.4× 164 1.4× 81 0.9× 49 1.2k
Mohammad Amin Rezvanfar Iran 19 138 0.4× 234 0.8× 53 0.4× 257 2.2× 204 2.4× 43 1.1k
Kellie A. Woodling United States 15 327 1.0× 165 0.5× 40 0.3× 19 0.2× 39 0.5× 25 835
Mohamed Montassar Lasram Tunisia 16 168 0.5× 167 0.6× 82 0.6× 24 0.2× 47 0.5× 24 960
Soon Young Han South Korea 26 1.0k 3.1× 402 1.3× 57 0.4× 66 0.6× 162 1.9× 56 1.8k

Countries citing papers authored by Shanlei Qiao

Since Specialization
Citations

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

Fields of papers citing papers by Shanlei Qiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanlei Qiao

This figure shows the co-authorship network connecting the top 25 collaborators of Shanlei Qiao. A scholar is included among the top collaborators of Shanlei Qiao 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 Shanlei Qiao. Shanlei Qiao 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.
Cao, Libo, Liping Zeng, Yaoxuan Wang, et al.. (2024). U2-Net and ResNet50-Based Automatic Pipeline for Bacterial Colony Counting. Microorganisms. 12(1). 201–201. 3 indexed citations
2.
Chen, Xiaolu, et al.. (2021). Deep convolutional neural network: a novel approach for the detection of Aspergillus fungi via stereomicroscopy. The Journal of Microbiology. 59(6). 563–572. 15 indexed citations
3.
Zhu, Jun, Lei Tang, Shanlei Qiao, et al.. (2020). Low-dose methylmercury exposure impairs the locomotor activity of zebrafish: Role of intestinal inositol metabolism. Environmental Research. 190. 110020–110020. 22 indexed citations
4.
Qiu, Yunping, Wei Jia, Qiong Li, et al.. (2020). A targeted metabolomic protocol for short-chain fatty acids and branched-chain amino acids. UNC Libraries.
5.
Zhu, Jun, Jiansheng Zhu, Li Wang, et al.. (2019). Comparative effects of mercury chloride and methylmercury exposure on early neurodevelopment in zebrafish larvae. RSC Advances. 9(19). 10766–10775. 29 indexed citations
6.
Zhang, Zhan, Di Wang, Shanlei Qiao, et al.. (2017). Metabolic and microbial signatures in rat hepatocellular carcinoma treated with caffeic acid and chlorogenic acid. Scientific Reports. 7(1). 4508–4508. 41 indexed citations
7.
Qiao, Shanlei, Wei Wu, Minjian Chen, et al.. (2017). Seminal plasma metabolomics approach for the diagnosis of unexplained male infertility. PLoS ONE. 12(8). e0181115–e0181115. 50 indexed citations
8.
Zhang, Xiaobo, et al.. (2016). Application of metabolomics in establishing primary nephrotic syndrome diagnosis model. 32(5). 334–338. 1 indexed citations
9.
Qiao, Shanlei, et al.. (2015). [A investigation of thirdhand smoke pollution in 3 types of places of Nanjing, 2014].. PubMed. 49(1). 31–5. 6 indexed citations
10.
Xu, Bo, Minjian Chen, Mengmeng Yao, et al.. (2015). Metabolomics reveals metabolic changes in male reproductive cells exposed to thirdhand smoke. Scientific Reports. 5(1). 15512–15512. 34 indexed citations
11.
Liu, Jing, Chunhui Ni, Lu Ding, et al.. (2014). [Effects of carbon disulfide inhalation on lipid levels of ApoE gene knockout mice and C57BL/6J mice].. PubMed. 32(11). 844–7. 1 indexed citations
12.
Chen, Minjian, Kun Zhou, Xiaojiao Chen, et al.. (2014). Metabolomic Analysis Reveals Metabolic Changes Caused by Bisphenol A in Rats. Toxicological Sciences. 138(2). 256–267. 41 indexed citations
13.
Chen, Minjian, Rong Tang, Guangbo Fu, et al.. (2013). Association of exposure to phenols and idiopathic male infertility. Journal of Hazardous Materials. 250-251. 115–121. 123 indexed citations
14.
Zheng, Xiaojiao, Yunping Qiu, Wei Zhong, et al.. (2013). A targeted metabolomic protocol for short-chain fatty acids and branched-chain amino acids. Metabolomics. 9(4). 818–827. 201 indexed citations
15.
Yu, Ying, Jinhui Xu, Yuan Liu, Shanlei Qiao, & Yun Chen. (2012). A liquid chromatography–tandem mass spectrometry method for the determination of nodularin-R in human plasma and its preliminary clinical application. Clinica Chimica Acta. 413(9-10). 894–900. 6 indexed citations
16.
Chen, Minjian, Pengfei Zhu, Bin Xu, et al.. (2012). Determination of Nine Environmental Phenols in Urine by Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry. Journal of Analytical Toxicology. 36(9). 608–615. 59 indexed citations
17.
Chen, Yun, Shanlei Qiao, & Ce Wang. (2009). Fragmentation of peptides with intra-chain disulfide bonds in triple quadrupole mass spectrometry and its quantitative application to biological samples. International Journal of Mass Spectrometry. 288(1-3). 68–74. 10 indexed citations
18.
Han, Yan, Yankai Xia, Pengfei Zhu, et al.. (2009). Reproductive hormones in relation to polycyclic aromatic hydrocarbon (PAH) metabolites among non-occupational exposure of males. The Science of The Total Environment. 408(4). 768–773. 29 indexed citations
19.
Zhu, Pengfei, Yankai Xia, Yan Han, et al.. (2009). Relationship between urinary metabolites of polycyclic aromatic hydrocarbons and thyroid hormone levels in Chinese non-occupational exposure adult males. Chemosphere. 77(7). 883–888. 30 indexed citations
20.
Qiao, Shanlei. (2007). Enantiospecific analysis of pregabalin by HPLC with chiral precolumn derivatization. Zhongguo yaoke daxue xuebao. 3 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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