Benjamin M. Good
Impact in
- Virology top 1%
- HIV Research and Treatment
-
- Mobile Crowdsensing and Crowdsourcing
Papers in
-
- Biomedical Text Mining and Ontologies 24
- Bioinformatics and Genomic Networks 9
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- Semantic Web and Ontologies 9
- Co-authors
- Andrew I. Su (28 shared papers)Satish K. Pillai (5 shared papers)Douglas D. Richman (5 shared papers)Mark D. Wilkinson (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)PLoS ONE (3 papers)Journal of Virology (3 papers)BMC Bioinformatics (2 papers)
- Partner nations
- United StatesCanadaSwitzerland
In The Last Decade
Benjamin M. Good
51 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 144
- Virology 471
- Computer Science Applications 112
- Infectious Diseases 285
- Information Systems and Management 81
- Communication 68
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 52 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 136 | |
| 2 | 2007 | 120 | |
| 3 | 2005 | 118 | |
| 4 | 2003 | 106 | |
| 5 | 2013 | 96 | |
| 6 | 2006 | 84 | |
| 7 | 2005 | 83 | |
| 8 | 2019 | 70 | |
| 9 | 2015 | 68 | |
| 10 | 2011 | 57 | |
| 11 | 2006 | 56 | |
| 12 | 2020 | 55 | |
| 13 | 2014 | 46 | |
| 14 | 2011 | 37 | |
| 15 | 2016 | 31 | |
| 16 | 2014 | 28 | |
| 17 | 2014 | 27 | |
| 18 | 2006 | 21 | |
| 19 | 2004 | 20 | |
| 20 | 2005 | 20 |
About Benjamin M. Good
Benjamin M. Good is a scholar working on Molecular Biology, Artificial Intelligence, Communication, Infectious Diseases and Virology, having authored 52 papers that have together received 1.5k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (24 papers), Bioinformatics and Genomic Networks (9 papers), Semantic Web and Ontologies (9 papers), Wikis in Education and Collaboration (8 papers), HIV Research and Treatment (6 papers), Mobile Crowdsensing and Crowdsourcing (6 papers), Scientific Computing and Data Management (5 papers) and HIV/AIDS Research and Interventions (4 papers). The work is most often cited by research in Virology (471 citations), Computer Science Applications (112 citations), Infectious Diseases (285 citations), Information Systems and Management (81 citations) and Communication (68 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, Douglas D. Richman, Mark D. Wilkinson, Thomas Hentrich, Jacques Corbeil, Davey M. Smith, Joseph K. Wong, Erik Clarke and Sergei L. Kosakovsky Pond. Their work appears in journals such as Database, Bioinformatics, PLoS ONE, Journal of Virology and BMC Bioinformatics.
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.