Nicholas Link
Impact in
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 1
- SARS-CoV-2 detection and testing 1
-
- Biomedical Text Mining and Ontologies 2
- Bioinformatics and Genomic Networks 1
- Co-authors
- Mauricio Santillana (2 shared papers)Pablo M. De Salazar (1 shared paper)Chuan Hong (2 shared papers)Tianrun Cai (2 shared papers)Jiehuan Sun (2 shared papers)Kelly Cho (2 shared papers)Tianxi Cai (2 shared papers)Katherine P. Liao (2 shared papers)
- Journals
- Journal of Public Health Management and Practice (1 paper)Journal of the American Medical Informatics Association (1 paper)PLoS Computational Biology (1 paper)International Journal of Medical Informatics (1 paper)Communications Medicine (1 paper)
- Partner nations
- United StatesChinaSpain
In The Last Decade
Nicholas Link
5 papers receiving 114 citations
Peers
Comparison fields: 5 of 48
- Modeling and Simulation 32
- Health Information Management 12
- Health 16
- Infectious Diseases 32
- Health Informatics 2
Countries citing papers authored by Nicholas Link
This map shows the geographic impact of Nicholas Link'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 Nicholas Link with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Link more than expected).
Fields of papers citing papers by Nicholas Link
This network shows the impact of papers produced by Nicholas Link. 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 Nicholas Link. The network helps show where Nicholas Link may publish in the future.
Co-authors
The 25 scholars most cited alongside Nicholas Link, 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 | 2019 | 56 | |
| 2 | 2021 | 29 | |
| 3 | 2021 | 18 | |
| 4 | 2022 | 8 | |
| 5 | 2024 | 4 |
About Nicholas Link
Nicholas Link is a scholar working on Infectious Diseases, Molecular Biology, Modeling and Simulation, Health and Epidemiology, having authored 5 papers that have together received 115 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (2 papers), Biomedical Text Mining and Ontologies (2 papers), Advanced Text Analysis Techniques (1 paper), Bioinformatics and Genomic Networks (1 paper), COVID-19 diagnosis using AI (1 paper), Influenza Virus Research Studies (1 paper), SARS-CoV-2 and COVID-19 Research (1 paper) and SARS-CoV-2 detection and testing (1 paper). The work is most often cited by research in Modeling and Simulation (32 citations), Health Information Management (12 citations), Health (16 citations), Infectious Diseases (32 citations) and Health Informatics (2 citations). Nicholas Link has collaborated with scholars based in United States, China and Spain. Frequent co-authors include Mauricio Santillana, Pablo M. De Salazar, Chuan Hong, Tianrun Cai, Jiehuan Sun, Kelly Cho, Tianxi Cai, Katherine P. Liao, Alessandro Vespignani and Christopher J. O’Donnell. Their work appears in journals such as Journal of Public Health Management and Practice, Journal of the American Medical Informatics Association, PLoS Computational Biology, International Journal of Medical Informatics and Communications Medicine.
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.