Aixia Yan
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Spectroscopy top 5%
- Analytical Chemistry and Chromatography
Papers in
-
- Computational Drug Discovery Methods 58
-
- Machine Learning in Bioinformatics 11
- Co-authors
- Johann Gasteiger (7 shared papers)Zhi Wang (4 shared papers)Zhide Hu (8 shared papers)Xiaoying Hu (8 shared papers)Maolin Wang (11 shared papers)Liang Hu (3 shared papers)Yujia Tian (11 shared papers)Robert C. Glen (2 shared papers)
- Journals
- SAR and QSAR in environmental research (13 papers)Molecular Diversity (12 papers)Molecular Informatics (7 papers)Combinatorial Chemistry & High Throughput Screening (7 papers)Bioorganic & Medicinal Chemistry Letters (5 papers)
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Aixia Yan
99 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 142
- Computational Theory and Mathematics 727
- Spectroscopy 238
- Analytical Chemistry 103
- Virology 38
- Pharmacology 70
Countries citing papers authored by Aixia Yan
This map shows the geographic impact of Aixia Yan'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 Aixia Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aixia Yan more than expected).
Fields of papers citing papers by Aixia Yan
This network shows the impact of papers produced by Aixia Yan. 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 Aixia Yan. The network helps show where Aixia Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Aixia Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 104 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 122 | |
| 2 | 2008 | 104 | |
| 3 | 2006 | 84 | |
| 4 | 2011 | 83 | |
| 5 | 2012 | 50 | |
| 6 | 2003 | 47 | |
| 7 | 2010 | 47 | |
| 8 | 2004 | 34 | |
| 9 | 2012 | 34 | |
| 10 | 2014 | 32 | |
| 11 | 2013 | 30 | |
| 12 | 2000 | 29 | |
| 13 | 1999 | 29 | |
| 14 | 2013 | 28 | |
| 15 | 2000 | 26 | |
| 16 | 2012 | 26 | |
| 17 | 2019 | 26 | |
| 18 | 2000 | 25 | |
| 19 | 2011 | 25 | |
| 20 | 2016 | 23 |
About Aixia Yan
Aixia Yan is a scholar working on Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Pharmacology and Spectroscopy, having authored 104 papers that have together received 1.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (58 papers), Analytical Chemistry and Chromatography (14 papers), HIV/AIDS drug development and treatment (11 papers), Machine Learning in Bioinformatics (11 papers), Synthesis and biological activity (10 papers), Advanced Chemical Sensor Technologies (10 papers), HER2/EGFR in Cancer Research (7 papers) and Inflammatory mediators and NSAID effects (7 papers). The work is most often cited by research in Computational Theory and Mathematics (727 citations), Spectroscopy (238 citations), Analytical Chemistry (103 citations), Virology (38 citations) and Pharmacology (70 citations). Aixia Yan has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Johann Gasteiger, Zhi Wang, Zhide Hu, Xiaoying Hu, Maolin Wang, Liang Hu, Yujia Tian, Robert C. Glen, Liyu Wang and Min Zhong. Their work appears in journals such as SAR and QSAR in environmental research, Molecular Diversity, Molecular Informatics, Combinatorial Chemistry & High Throughput Screening and Bioorganic & Medicinal Chemistry Letters.
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.