Dai-Ling Wu

903 citations
12 papers · 701 · 1 hit paper · h-index 10

Impact in

Papers in

Dai-Ling Wu

12 papers receiving 692 citations

Dai-Ling Wu's Hit Papers

From river to groundwater: Antibiotics pollution, resistance prevalence, and source tracking 2025 · 23 citations
230Years since publication5101520

Peers

Dai-Ling Wu
Comparison fields: 5 of 76
  • Pollution 509
  • Molecular Medicine 214
  • Applied Microbiology and Biotechnology 51
  • Health, Toxicology and Mutagenesis 88
  • Ecology 138
Replace Ya He with:
Ya He China
Lu-Xi He China
Linyun Li China
Fang-Zhou Gao China
Xinyi Shuai China
Zejun Lin China
Nuohan Xu China
Isobel C. Stanton United Kingdom
Tingzhang Wang China
Norman Hembach Germany
Dai-Ling Wu relative to Ya He China Ya He's profile →
Citations per field
00.5×1.5×
Ya He · 1×
Citations per year

Countries citing papers authored by Dai-Ling Wu

Since Specialization
Citations

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

Fields of papers citing papers by Dai-Ling Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dai-Ling Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dai-Ling Wu Line = papers co-authored together Dai-Ling Wu links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2021142
2 2020116
3 2020106
4 202096
5 202180
6 202163
7 202142
8
From river to groundwater: Antibiotics pollution, resistance prevalence, and source tracking
Hit paper breakdown →
202523
9 202316
10 202015
11 20241
12 20251

About Dai-Ling Wu

Dai-Ling Wu is a scholar working on Pollution, Molecular Medicine, Ecology, Molecular Biology and Pharmacology, having authored 12 papers that have together received 701 indexed citations. Recurring topics across this work include Pharmaceutical and Antibiotic Environmental Impacts (12 papers), Antibiotic Resistance in Bacteria (7 papers), Water Treatment and Disinfection (2 papers), Ethics in Clinical Research (2 papers), Aquaculture disease management and microbiota (2 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers), Bacteriophages and microbial interactions (2 papers) and Gut microbiota and health (2 papers). The work is most often cited by research in Pollution (509 citations), Molecular Medicine (214 citations), Applied Microbiology and Biotechnology (51 citations), Health, Toxicology and Mutagenesis (88 citations) and Ecology (138 citations). Dai-Ling Wu has collaborated with scholars based in China and Netherlands. Frequent co-authors include Guang‐Guo Ying, Liang-Ying He, Haiyan Zou, Fang-Zhou Gao, Hong Bai, Min Zhang, Lu-Xi He, You‐Sheng Liu, Maosheng Yao and Min Zhang. Their work appears in journals such as The Science of The Total Environment, Environment International, Environmental Pollution, Ecotoxicology and Environmental Safety and Journal of Chromatography B.

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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