Haixia Dang

31 total papers · 1.0k total citations
20 papers, 789 citations indexed

About

Haixia Dang is a scholar working on Complementary and alternative medicine, Pharmacology and Molecular Biology. According to data from OpenAlex, Haixia Dang has authored 20 papers receiving a total of 789 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Complementary and alternative medicine, 7 papers in Pharmacology and 6 papers in Molecular Biology. Recurrent topics in Haixia Dang's work include Flavonoids in Medical Research (4 papers), Plant-based Medicinal Research (4 papers) and Traditional Chinese Medicine Analysis (4 papers). Haixia Dang is often cited by papers focused on Flavonoids in Medical Research (4 papers), Plant-based Medicinal Research (4 papers) and Traditional Chinese Medicine Analysis (4 papers). Haixia Dang collaborates with scholars based in China, Canada and United States. Haixia Dang's co-authors include Xinmin Liu, Qiong Wang, William Jia, Yuqing Wang, Ying Chen, Liwei Wang, Julio Rubio, Gustavo F. Gonzáles, Shilin Chen and Weimin Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Brain Research and Journal of Ethnopharmacology.

In The Last Decade

Haixia Dang

19 papers receiving 757 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Haixia Dang	265	190	142	136	120	20	789
Xin Lan	271 1.0×	34 0.2×	39 0.3×	194 1.4×	26 0.2×	27	847
J.S. Bapna	105 0.4×	48 0.3×	64 0.5×	24 0.2×	60 0.5×	45	674
Yang Yue	380 1.4×	90 0.5×	110 0.8×	21 0.2×	41 0.3×	19	845
Anantha Naik Nagappa	134 0.5×	38 0.2×	74 0.5×	250 1.8×	31 0.3×	40	708
Wenyuan Zhang	268 1.0×	35 0.2×	62 0.4×	162 1.2×	29 0.2×	24	685
Otilia J.F. Banji	139 0.5×	122 0.6×	85 0.6×	19 0.1×	117 1.0×	47	727
Wen-Fei Chiou	249 0.9×	135 0.7×	184 1.3×	121 0.9×	82 0.7×	22	819
Mohammad Fahim Kadir	120 0.5×	247 1.3×	63 0.4×	73 0.5×	111 0.9×	28	819
Yo‐Chan Ahn	175 0.7×	127 0.7×	93 0.7×	26 0.2×	166 1.4×	30	845
Manas Das	174 0.7×	47 0.2×	158 1.1×	94 0.7×	76 0.6×	35	725

Countries citing papers authored by Haixia Dang

Since Specialization

Citations

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

Fields of papers citing papers by Haixia Dang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haixia Dang

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

All Works

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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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