Daniel Sanford
Impact in
- Biotechnology top 10%
- Microbial Inactivation Methods
- Infectious Diseases top 10%
- Viral Infections and Outbreaks Research
- SARS-CoV-2 and COVID-19 Research
Papers in
-
- Bacillus and Francisella bacterial research 9
-
- Viral Infections and Outbreaks Research 7
- Viral Infections and Vectors 5
- Co-authors
- James W. DeWille (2 shared papers)Gabriel Meister (2 shared papers)Andrew Chen (1 shared paper)John Zhong (1 shared paper)Thi-Sau Migone (1 shared paper)Jason Mott (1 shared paper)Maggie Lewis (1 shared paper)Matt Devalaraja (1 shared paper)
- Journals
- Vaccine (3 papers)Antimicrobial Agents and Chemotherapy (3 papers)PLoS neglected tropical diseases (2 papers)Biology (2 papers)Vaccines (2 papers)
- Partner nations
- United StatesNetherlands
In The Last Decade
Daniel Sanford
28 papers receiving 601 citations
Peers
Comparison fields: 5 of 90
- Biotechnology 76
- Infectious Diseases 157
- Virology 34
- Endocrinology 27
- Health Informatics 7
Countries citing papers authored by Daniel Sanford
This map shows the geographic impact of Daniel Sanford'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 Daniel Sanford with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Sanford more than expected).
Fields of papers citing papers by Daniel Sanford
This network shows the impact of papers produced by Daniel Sanford. 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 Daniel Sanford. The network helps show where Daniel Sanford may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Sanford, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 202 | |
| 2 | 2004 | 43 | |
| 3 | 2013 | 34 | |
| 4 | 2016 | 33 | |
| 5 | 2004 | 29 | |
| 6 | 2016 | 29 | |
| 7 | 2013 | 25 | |
| 8 | 2017 | 22 | |
| 9 | 2017 | 21 | |
| 10 | 2019 | 21 | |
| 11 | 2018 | 19 | |
| 12 | 2021 | 19 | |
| 13 | 2011 | 18 | |
| 14 | 2020 | 17 | |
| 15 | 2010 | 16 | |
| 16 | 2013 | 13 | |
| 17 | 2019 | 11 | |
| 18 | 2022 | 11 | |
| 19 | 2023 | 9 | |
| 20 | 2022 | 9 |
About Daniel Sanford
Daniel Sanford is a scholar working on Molecular Biology, Infectious Diseases, Cellular and Molecular Neuroscience, Endocrine and Autonomic Systems and Epidemiology, having authored 30 papers that have together received 635 indexed citations. Recurring topics across this work include Bacillus and Francisella bacterial research (9 papers), Viral Infections and Outbreaks Research (7 papers), Regulation of Appetite and Obesity (5 papers), Viral Infections and Vectors (5 papers), Neuropeptides and Animal Physiology (4 papers), Yersinia bacterium, plague, ectoparasites research (3 papers), Microbial Inactivation Methods (3 papers) and Burkholderia infections and melioidosis (3 papers). The work is most often cited by research in Biotechnology (76 citations), Infectious Diseases (157 citations), Virology (34 citations), Endocrinology (27 citations) and Health Informatics (7 citations). Daniel Sanford has collaborated with scholars based in United States and Netherlands. Frequent co-authors include James W. DeWille, Gabriel Meister, Andrew Chen, John Zhong, Thi-Sau Migone, Jason Mott, Maggie Lewis, Matt Devalaraja, Sally D. Bolmer and Stephen J. Ullrich. Their work appears in journals such as Vaccine, Antimicrobial Agents and Chemotherapy, PLoS neglected tropical diseases, Biology and Vaccines.
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.