Li‐Tang Qin

1.4k total citations
65 papers, 1.1k citations indexed

About

Li‐Tang Qin is a scholar working on Pollution, Health, Toxicology and Mutagenesis and Computational Theory and Mathematics. According to data from OpenAlex, Li‐Tang Qin has authored 65 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Pollution, 29 papers in Health, Toxicology and Mutagenesis and 16 papers in Computational Theory and Mathematics. Recurrent topics in Li‐Tang Qin's work include Pharmaceutical and Antibiotic Environmental Impacts (18 papers), Environmental Toxicology and Ecotoxicology (16 papers) and Computational Drug Discovery Methods (16 papers). Li‐Tang Qin is often cited by papers focused on Pharmaceutical and Antibiotic Environmental Impacts (18 papers), Environmental Toxicology and Ecotoxicology (16 papers) and Computational Drug Discovery Methods (16 papers). Li‐Tang Qin collaborates with scholars based in China, United Kingdom and South Korea. Li‐Tang Qin's co-authors include Shu‐Shen Liu, Lingyun Mo, Honghu Zeng, Yanpeng Liang, Jin Zhang, Hailing Liu, Yuhan Chen, Junfeng Dai, Dunqiu Wang and Qianfen Xiao and has published in prestigious journals such as The Science of The Total Environment, Journal of Hazardous Materials and Environmental Pollution.

In The Last Decade

Li‐Tang Qin

60 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Li‐Tang Qin China 19 398 397 203 137 127 65 1.1k
Yuanhui Zhao China 22 503 1.3× 483 1.2× 183 0.9× 173 1.3× 176 1.4× 61 1.3k
Xianhai Yang China 22 468 1.2× 572 1.4× 227 1.1× 179 1.3× 132 1.0× 61 1.3k
Melek Türker Saçan Türkiye 18 297 0.7× 266 0.7× 211 1.0× 116 0.8× 74 0.6× 40 864
Lingyun Mo China 16 317 0.8× 275 0.7× 117 0.6× 92 0.7× 106 0.8× 49 796
Anna Lombardo Italy 25 342 0.9× 495 1.2× 574 2.8× 175 1.3× 209 1.6× 49 1.4k
Alessandro Sangion Canada 18 292 0.7× 360 0.9× 428 2.1× 197 1.4× 180 1.4× 30 1.1k
Monika Nendza Germany 19 411 1.0× 696 1.8× 360 1.8× 163 1.2× 199 1.6× 47 1.4k
Xiaoming Zou China 18 510 1.3× 205 0.5× 62 0.3× 87 0.6× 134 1.1× 48 1.0k
Geoff Hodges United Kingdom 15 472 1.2× 333 0.8× 131 0.6× 173 1.3× 121 1.0× 40 1.0k
Mike Comber United Kingdom 20 492 1.2× 696 1.8× 252 1.2× 233 1.7× 99 0.8× 29 1.3k

Countries citing papers authored by Li‐Tang Qin

Since Specialization
Citations

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

Fields of papers citing papers by Li‐Tang Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li‐Tang Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Li‐Tang Qin. A scholar is included among the top collaborators of Li‐Tang Qin 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 Li‐Tang Qin. Li‐Tang Qin 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.
Chen, Qing, et al.. (2025). Degradation of β-HCH by Enterobacter sp. CS01: Characteristics, mechanism and application in soil remediation. Biochemical Engineering Journal. 217. 109673–109673. 1 indexed citations
2.
Mo, Lingyun, Qian Yang, Ying Hou, et al.. (2025). Oxidative stress mechanisms underlying temporal hormesis effects induced by binary antibiotic mixtures on Scenedesmus obliquus. Ecotoxicology and Environmental Safety. 291. 117889–117889. 3 indexed citations
3.
Li, Yabin, Li‐Tang Qin, Xiran Li, et al.. (2025). Response of aerobic granular sludge to organic loading rate under micro-electric stimulation environment. Frontiers of Environmental Science & Engineering. 19(5). 1 indexed citations
4.
Qin, Li‐Tang, Honghu Zeng, Yi Liang, et al.. (2025). Ecotoxicological risk assessment of N-nitrosamines to Selenastrum capricornutum in surface waters: Insights into toxicity mechanisms and environmental Implications. Ecotoxicology and Environmental Safety. 296. 118179–118179.
5.
Liang, Yanpeng, Honghu Zeng, Huanfang Huang, et al.. (2024). Organochlorine pesticides in water and sediment at a typical karst wetland in Southwest China. Journal of Geochemical Exploration. 264. 107519–107519. 5 indexed citations
6.
Qin, Li‐Tang, et al.. (2024). Toxic interactions at the physiological and biochemical levels of green algae under stress of mixtures of three azole fungicides. The Science of The Total Environment. 926. 171771–171771. 4 indexed citations
7.
Liu, Yongan, et al.. (2024). Predicting the Time-Dependent Toxicities of Binary Mixtures of Five Antibiotics to Vibrio qinghaiensis sp.-Q67 Based on the QSAR Model. Environment & Health. 2(7). 465–473. 6 indexed citations
8.
Qin, Li‐Tang, et al.. (2024). Classification and regression machine learning models for predicting the combined toxicity and interactions of antibiotics and fungicides mixtures. Environmental Pollution. 360. 124565–124565. 13 indexed citations
9.
Liu, Min, et al.. (2023). Toxicity interactions of azole fungicide mixtures on Chlorella pyrenoidosa . Environmental Toxicology. 38(7). 1509–1519. 8 indexed citations
10.
11.
Mo, Lingyun, Yongan Liu, Jie Zhu, et al.. (2020). Benefits from hazards, benefits from nothing, and benefits from benefits: the combined effects of five quaternary ammonium compounds to Vibrio qinghaiensis Q67. Environmental Sciences Europe. 32(1). 23 indexed citations
12.
Qin, Li‐Tang, et al.. (2019). Toxicological Interactions of Organophosphorus Pesticides Mixtures to Chlorella pyrenoidosa. Asian Journal of Ecotoxicology. 121–129. 3 indexed citations
13.
Qin, Li‐Tang, et al.. (2018). QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide. Chemosphere. 198. 122–129. 60 indexed citations
14.
Fu, Xin, et al.. (2018). Distribution of organochlorine pesticides(OCPs) in the water body of Huixian Karst wetland of Guilin and environmental risk assessment of OCP mixtures.. Nongye huanjing kexue xuebao. 37(5). 974–983. 3 indexed citations
15.
Mo, Lingyun, et al.. (2017). Joint toxicity of six common heavy metals to Chlorella pyrenoidosa. Environmental Science and Pollution Research. 26(30). 30554–30560. 18 indexed citations
16.
Zhang, Yahui, et al.. (2017). Toxicity of organophosphorus pesticides to Neocaridina denticulate and species sensitivity analysis.. China Environmental Science. 37(2). 745–753. 1 indexed citations
17.
Mo, Lingyun, et al.. (2016). Quantitative Characterization of the Toxicities of Cd-Ni and Cd-Cr Binary Mixtures Using Combination Index Method. BioMed Research International. 2016. 1–6. 9 indexed citations
18.
Qin, Li‐Tang. (2013). Internal and external validtions of QSAR model: Review. Environmental Chemistry. 3 indexed citations
19.
Liu, Shu‐Shen, et al.. (2012). APTox: Assessment and Prediction on Toxicity of Chemical Mixtures. Acta Chimica Sinica. 70(14). 1511–1511. 85 indexed citations
20.
Qin, Li‐Tang. (2010). Toxicities of Binary Mixtures Including at Least One Component with J-Shaped Dose-Response Curve. Asian Journal of Ecotoxicology. 1 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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