Danlian Wu

586 total citations
11 papers, 490 citations indexed

About

Danlian Wu is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cancer Research. According to data from OpenAlex, Danlian Wu has authored 11 papers receiving a total of 490 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Cancer Research. Recurrent topics in Danlian Wu's work include Stress Responses and Cortisol (2 papers), Effects and risks of endocrine disrupting chemicals (2 papers) and Carcinogens and Genotoxicity Assessment (2 papers). Danlian Wu is often cited by papers focused on Stress Responses and Cortisol (2 papers), Effects and risks of endocrine disrupting chemicals (2 papers) and Carcinogens and Genotoxicity Assessment (2 papers). Danlian Wu collaborates with scholars based in China. Danlian Wu's co-authors include Li‐Juan Zhu, Dong‐Ya Zhu, Chun‐Xia Luo, Yao Hu, Hai‐Yin Wu, Jing Zhang, Wei Qu, Zhenguo Zhao, Sijin Chen and Lijin Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and Journal of Neurochemistry.

In The Last Decade

Danlian Wu

10 papers receiving 485 citations

Peers

Danlian Wu
Comparison fields: 5 of 81
  • Molecular Biology 129
  • Physiology 124
  • Cellular and Molecular Neuroscience 115
  • Behavioral Neuroscience 107
  • Biological Psychiatry 104
Replace José Fernando de Oliveira with:
José Fernando de Oliveira Brazil
Agnieszka Zelek-Molik Poland
Cedomir Todorovic United States
Kaustuv Saha United States
Olalekan M. Ogundele Nigeria
Francesco Fazio Italy
Catherine Cohen‐Solal France
Shengnan Kuang China
Marina N. Karpenko Russia
Tangeng Ma United States
José Fernando de Oliveira Brazil View profile →
Citations per field, relative to Danlian Wu
Danlian Wu · 1×
Citations per year, relative to Danlian Wu
Danlian Wu · 1×

Countries citing papers authored by Danlian Wu

Since Specialization
Citations

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

Fields of papers citing papers by Danlian Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danlian Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Danlian Wu. A scholar is included among the top collaborators of Danlian Wu 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 Danlian Wu. Danlian Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
# Work Indexed citations
1 0
2 22
3 1
4 6
5 62
6 51
7 31
8 34
9 77
10 84
11 122

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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