Edison Ong
Impact in
- Health Informatics top 5%
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
Papers in
-
- Biomedical Text Mining and Ontologies 14
- vaccines and immunoinformatics approaches 14
- Bioinformatics and Genomic Networks 12
- Machine Learning in Bioinformatics 5
-
- Tuberculosis Research and Epidemiology 5
- SARS-CoV-2 and COVID-19 Research 4
- Co-authors
- Yongqun He (31 shared papers)Anthony Huffman (6 shared papers)Zuoshuang Xiang (5 shared papers)Haihe Wang (3 shared papers)Jie Zheng (5 shared papers)Bin Zhao (3 shared papers)Yu Lin (4 shared papers)Zhaohui Ni (2 shared papers)
- Journals
- BMC Bioinformatics (5 papers)Frontiers in Immunology (3 papers)Nucleic Acids Research (3 papers)Infection Genetics and Evolution (2 papers)PLoS ONE (2 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Edison Ong
39 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 118
- Health Informatics 40
- Infectious Diseases 350
- Molecular Medicine 75
- Molecular Biology 664
- Modeling and Simulation 42
Countries citing papers authored by Edison Ong
This map shows the geographic impact of Edison Ong'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 Edison Ong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edison Ong more than expected).
Fields of papers citing papers by Edison Ong
This network shows the impact of papers produced by Edison Ong. 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 Edison Ong. The network helps show where Edison Ong may publish in the future.
Co-authors
The 25 scholars most cited alongside Edison Ong, 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 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 293 | |
| 2 | 2018 | 126 | |
| 3 | 2016 | 97 | |
| 4 | 2020 | 94 | |
| 5 | 2021 | 77 | |
| 6 | 2020 | 69 | |
| 7 | 2017 | 54 | |
| 8 | 2018 | 47 | |
| 9 | 2020 | 30 | |
| 10 | 2017 | 23 | |
| 11 | 2014 | 18 | |
| 12 | 2014 | 17 | |
| 13 | 2019 | 17 | |
| 14 | 2023 | 16 | |
| 15 | 2020 | 16 | |
| 16 | 2022 | 12 | |
| 17 | 2021 | 11 | |
| 18 | 2017 | 9 | |
| 19 | 2019 | 8 | |
| 20 | 2017 | 7 |
About Edison Ong
Edison Ong is a scholar working on Molecular Biology, Infectious Diseases, Artificial Intelligence, Epidemiology and Computational Theory and Mathematics, having authored 41 papers that have together received 1.1k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (14 papers), vaccines and immunoinformatics approaches (14 papers), Bioinformatics and Genomic Networks (12 papers), Semantic Web and Ontologies (8 papers), Machine Learning in Bioinformatics (5 papers), Tuberculosis Research and Epidemiology (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Health Informatics (40 citations), Infectious Diseases (350 citations), Molecular Medicine (75 citations), Molecular Biology (664 citations) and Modeling and Simulation (42 citations). Edison Ong has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Yongqun He, Anthony Huffman, Zuoshuang Xiang, Haihe Wang, Jie Zheng, Bin Zhao, Yu Lin, Zhaohui Ni, Luonan Chen and Zhenhua Yang. Their work appears in journals such as BMC Bioinformatics, Frontiers in Immunology, Nucleic Acids Research, Infection Genetics and Evolution and PLoS ONE.
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.