Daniel C. Cannon
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
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- Neonatal and fetal brain pathology
- Neonatal Health and Biochemistry
Papers in
-
- Biomedical Text Mining and Ontologies 2
- Machine Learning in Bioinformatics 1
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- Neonatal and fetal brain pathology 3
- Pharmacological Effects and Toxicity Studies 2
- Co-authors
- Robin K. Ohls (5 shared papers)Robert J. Glass (1 shared paper)S E Wiedmeier (4 shared papers)Douglas K Owens (1 shared paper)Jean Lowe (4 shared papers)Victoria J. Davey (1 shared paper)Alan M. Garber (1 shared paper)David H. Ackley (2 shared papers)
- Journals
- PEDIATRICS (2 papers)Clinical Infectious Diseases (1 paper)JMIR Mental Health (1 paper)Pediatric Research (1 paper)Journal of Affective Disorders (1 paper)
- Partner nations
- United StatesDenmarkGermany
In The Last Decade
Daniel C. Cannon
14 papers receiving 278 citations
Peers
Comparison fields: 5 of 80
- Modeling and Simulation 47
- Pediatrics, Perinatology and Child Health 130
- Nephrology 28
- Hematology 44
- Genetics 28
Countries citing papers authored by Daniel C. Cannon
This map shows the geographic impact of Daniel C. Cannon'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 C. Cannon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel C. Cannon more than expected).
Fields of papers citing papers by Daniel C. Cannon
This network shows the impact of papers produced by Daniel C. Cannon. 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 C. Cannon. The network helps show where Daniel C. Cannon may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel C. Cannon, 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 | 2014 | 91 | |
| 2 | 2009 | 64 | |
| 3 | 2016 | 48 | |
| 4 | 2017 | 22 | |
| 5 | 2019 | 15 | |
| 6 | Pursue robust indefinite scalability | 2011 | 11 |
| 7 | 2021 | 8 | |
| 8 | 2019 | 7 | |
| 9 | 2012 | 7 | |
| 10 | 2021 | 6 | |
| 11 | 2017 | 5 | |
| 12 | 2002 | 3 | |
| 13 | 2017 | 2 | |
| 14 | 2024 | 1 |
About Daniel C. Cannon
Daniel C. Cannon is a scholar working on Molecular Biology, Pediatrics, Perinatology and Child Health, Psychiatry and Mental health, Computational Theory and Mathematics and Hardware and Architecture, having authored 14 papers that have together received 290 indexed citations. Recurring topics across this work include Bipolar Disorder and Treatment (3 papers), Neonatal and fetal brain pathology (3 papers), Pharmacological Effects and Toxicity Studies (2 papers), Parallel Computing and Optimization Techniques (2 papers), Cellular Automata and Applications (2 papers), Biomedical Text Mining and Ontologies (2 papers), Advanced Neuroimaging Techniques and Applications (1 paper) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Modeling and Simulation (47 citations), Pediatrics, Perinatology and Child Health (130 citations), Nephrology (28 citations), Hematology (44 citations) and Genetics (28 citations). Daniel C. Cannon has collaborated with scholars based in United States, Denmark and Germany. Frequent co-authors include Robin K. Ohls, Robert J. Glass, S E Wiedmeier, Douglas K Owens, Jean Lowe, Victoria J. Davey, Alan M. Garber, David H. Ackley, Janell Fuller and R D Christensen. Their work appears in journals such as PEDIATRICS, Clinical Infectious Diseases, JMIR Mental Health, Pediatric Research and Journal of Affective Disorders.
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.