Betty Huang
- Molecular Biology top 2%
- Ubiquitin and proteasome pathways 3
- Glycosylation and Glycoproteins Research 2
- Immunology top 5%
- Immune Cell Function and Interaction 3
- Cell Biology top 2%
- Cancer Research top 5%
- Plant Science top 5%
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- Monoclonal and Polyclonal Antibodies Research 9
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- SARS-CoV-2 and COVID-19 Research 3
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- Bacteriophages and microbial interactions 3
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- CAR-T cell therapy research 3
- Cancer-related Molecular Pathways 3
- Co-authors
- Paul D. SiebertKonstantin A. LukyanovA. Patricia CampbellSergey LukyanovYun‐Fai Chris LauLuda DiatchenkoAlex ChenchikЕ. Д. Свердлов
- Journals
- Science (1 paper)Proceedings of the National Academy of Sciences (3 papers)Journal of Biological Chemistry (3 papers)
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
Betty Huang
31 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Molecular Biology 2.8k
- Immunology 706
- Cell Biology 514
- Cancer Research 374
- Plant Science 798
Countries citing papers authored by Betty Huang
This map shows the geographic impact of Betty Huang'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 Betty Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Betty Huang more than expected).
Fields of papers citing papers by Betty Huang
This network shows the impact of papers produced by Betty Huang. 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 Betty Huang. The network helps show where Betty Huang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Betty Huang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 3 | |
| 2 | 2023 | 15 | |
| 3 | 2022 | 15 | |
| 4 | 2022 | 1 | |
| 5 | 2021 | 2 | |
| 6 | 2020 | 73 | |
| 7 | 2017 | 22 | |
| 8 | 2013 | 38 | |
| 9 | 2005 | 49 | |
| 10 | 2004 | 51 | |
| 11 | 2003 | 13 | |
| 12 | 2003 | 57 | |
| 13 | 2001 | 99 | |
| 14 | 2001 | 74 | |
| 15 | 2000 | 63 | |
| 16 | 1999 | 118 | |
| 17 | 1999 | 153 | |
| 18 | 1998 | 166 | |
| 19 | 1996 | 24 | |
| 20 | 1995 | 10 |
About Betty Huang
Betty Huang is a scholar working on Metals and Alloys, Radiology, Nuclear Medicine and Imaging and Immunology, having authored 31 papers that have together received 4.5k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (9 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Bacteriophages and microbial interactions (3 papers), CAR-T cell therapy research (3 papers), Immune Cell Function and Interaction (3 papers), Ubiquitin and proteasome pathways (3 papers), Cancer-related Molecular Pathways (3 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Molecular Biology (2.8k citations), Immunology (706 citations) and Cell Biology (514 citations). Betty Huang has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include Paul D. Siebert, Konstantin A. Lukyanov, A. Patricia Campbell, Sergey Lukyanov, Yun‐Fai Chris Lau, Luda Diatchenko, Alex Chenchik, Е. Д. Свердлов, Nadya G. Gurskaya and Ying Luo. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.