Benjamin M. Good
Impact in
- Virology top 1%
- HIV Research and Treatment
-
- Mobile Crowdsensing and Crowdsourcing
Papers in
-
- Biomedical Text Mining and Ontologies 25
- Bioinformatics and Genomic Networks 9
- Genomics and Phylogenetic Studies 5
-
- Semantic Web and Ontologies 10
- Co-authors
- Andrew I. Su (28 shared papers)Satish K. Pillai (5 shared papers)Mark D. Wilkinson (5 shared papers)Douglas D. Richman (5 shared papers)Thomas Hentrich (1 shared paper)Jacques Corbeil (3 shared papers)Davey M. Smith (3 shared papers)Joseph K. Wong (3 shared papers)
- Journals
- Database (8 papers)Bioinformatics (5 papers)Journal of Virology (3 papers)PLoS ONE (3 papers)Journal of Biomedical Semantics (2 papers)
- Partner nations
- United StatesCanadaSwitzerland
In The Last Decade
Benjamin M. Good
52 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 147
- Virology 482
- Computer Science Applications 123
- Infectious Diseases 300
- Information Systems and Management 96
- Communication 77
Countries citing papers authored by Benjamin M. Good
This map shows the geographic impact of Benjamin M. Good'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 Benjamin M. Good with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin M. Good more than expected).
Fields of papers citing papers by Benjamin M. Good
This network shows the impact of papers produced by Benjamin M. Good. 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 Benjamin M. Good. The network helps show where Benjamin M. Good may publish in the future.
Co-authors
The 25 scholars most cited alongside Benjamin M. Good, 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 163 | |
| 2 | 2007 | 123 | |
| 3 | 2005 | 122 | |
| 4 | 2003 | 107 | |
| 5 | 2013 | 104 | |
| 6 | 2006 | 87 | |
| 7 | 2005 | 87 | |
| 8 | 2015 | 75 | |
| 9 | 2019 | 73 | |
| 10 | 2006 | 69 | |
| 11 | 2011 | 64 | |
| 12 | 2020 | 62 | |
| 13 | 2014 | 52 | |
| 14 | 2011 | 39 | |
| 15 | 2016 | 35 | |
| 16 | 2014 | 33 | |
| 17 | 2014 | 29 | |
| 18 | 2006 | 25 | |
| 19 | 2017 | 22 | |
| 20 | 2005 | 22 |
About Benjamin M. Good
Benjamin M. Good is a scholar working on Molecular Biology, Artificial Intelligence, Communication, Infectious Diseases and Virology, having authored 53 papers that have together received 1.7k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (25 papers), Semantic Web and Ontologies (10 papers), Bioinformatics and Genomic Networks (9 papers), Wikis in Education and Collaboration (8 papers), HIV Research and Treatment (6 papers), Mobile Crowdsensing and Crowdsourcing (6 papers), Genomics and Phylogenetic Studies (5 papers) and Scientific Computing and Data Management (5 papers). The work is most often cited by research in Virology (482 citations), Computer Science Applications (123 citations), Infectious Diseases (300 citations), Information Systems and Management (96 citations) and Communication (77 citations). Benjamin M. Good has collaborated with scholars based in United States, Canada and Switzerland. Frequent co-authors include Andrew I. Su, Satish K. Pillai, Mark D. Wilkinson, Douglas D. Richman, Thomas Hentrich, Jacques Corbeil, Davey M. Smith, Joseph K. Wong, Salvatore Loguercio and Erik Clarke. Their work appears in journals such as Database, Bioinformatics, Journal of Virology, PLoS ONE and Journal of Biomedical Semantics.
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.