David Hua
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Virology top 2%
- HIV Research and Treatment
Papers in
-
- Glycosylation and Glycoproteins Research 12
- Genomics and Phylogenetic Studies 4
-
- Monoclonal and Polyclonal Antibodies Research 5
- Co-authors
- Heather Desaire (16 shared papers)Eden P. Go (12 shared papers)Heather Desaire (4 shared papers)Barton F. Haynes (3 shared papers)Hua‐Xin Liao (2 shared papers)S. Munir Alam (2 shared papers)Haiyan Chen (2 shared papers)Romana Jarošová (1 shared paper)
- Journals
- Journal of Proteome Research (5 papers)Analytical Chemistry (4 papers)Journal of Virology (3 papers)Cell Reports Physical Science (3 papers)Big Data and Cognitive Computing (2 papers)
- Partner nations
- United StatesAustraliaUnited Arab Emirates
In The Last Decade
David Hua
28 papers receiving 777 citations
Peers
Comparison fields: 5 of 86
- Health Informatics 86
- Virology 259
- Spectroscopy 179
- Molecular Biology 442
- Radiology, Nuclear Medicine and Imaging 131
Countries citing papers authored by David Hua
This map shows the geographic impact of David Hua'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 David Hua with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Hua more than expected).
Fields of papers citing papers by David Hua
This network shows the impact of papers produced by David Hua. 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 David Hua. The network helps show where David Hua may publish in the future.
Co-authors
The 25 scholars most cited alongside David Hua, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 100 | |
| 2 | 2013 | 89 | |
| 3 | 2015 | 81 | |
| 4 | 2023 | 71 | |
| 5 | 2012 | 67 | |
| 6 | 2017 | 66 | |
| 7 | 2023 | 54 | |
| 8 | 2013 | 42 | |
| 9 | 2014 | 36 | |
| 10 | 2008 | 36 | |
| 11 | 2023 | 31 | |
| 12 | 2022 | 16 | |
| 13 | 2019 | 14 | |
| 14 | 2019 | 14 | |
| 15 | 2017 | 12 | |
| 16 | 2019 | 11 | |
| 17 | 2020 | 10 | |
| 18 | 2021 | 9 | |
| 19 | 2023 | 8 | |
| 20 | 2018 | 4 |
About David Hua
David Hua is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Spectroscopy, Health Informatics and Virology, having authored 28 papers that have together received 791 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (12 papers), Advanced Proteomics Techniques and Applications (7 papers), Artificial Intelligence in Healthcare and Education (6 papers), HIV Research and Treatment (5 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Genomics and Phylogenetic Studies (4 papers), Carbohydrate Chemistry and Synthesis (4 papers) and Topic Modeling (3 papers). The work is most often cited by research in Health Informatics (86 citations), Virology (259 citations), Spectroscopy (179 citations), Molecular Biology (442 citations) and Radiology, Nuclear Medicine and Imaging (131 citations). David Hua has collaborated with scholars based in United States, Australia and United Arab Emirates. Frequent co-authors include Heather Desaire, Eden P. Go, Heather Desaire, Barton F. Haynes, Hua‐Xin Liao, S. Munir Alam, Haiyan Chen, Romana Jarošová, Noel Young and Simon Poon. Their work appears in journals such as Journal of Proteome Research, Analytical Chemistry, Journal of Virology, Cell Reports Physical Science and Big Data and Cognitive Computing.
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.