Daniel Merl
Impact in
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
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- Cancer, Hypoxia, and Metabolism
Papers in ⓘ
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- COVID-19 epidemiological studies 2
- Co-authors
- Marc Mangel (3 shared papers)Leah R. Johnson (3 shared papers)Robert B. Gramacy (3 shared papers)Mike West (2 shared papers)Jen‐Tsan Chi (1 shared paper)Donald E. Ayer (1 shared paper)Hanwei Yin (1 shared paper)Julia Ling-Yu Chen (1 shared paper)
- Journals
- Journal of Statistical Software (1 paper)Bayesian Analysis (1 paper)Computational Statistics & Data Analysis (1 paper)PLoS Genetics (1 paper)Journal of the American Statistical Association (1 paper)
- Partner nations
- United StatesGermanyTaiwan
In The Last Decade
Daniel Merl
11 papers receiving 323 citations
Peers
Comparison fields: 5 of 121
- Modeling and Simulation 25
- Cancer Research 50
- Computer Networks and Communications 53
- Statistics and Probability 14
- Information Systems 37
Countries citing papers authored by Daniel Merl
This map shows the geographic impact of Daniel Merl'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 Merl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Merl more than expected).
Fields of papers citing papers by Daniel Merl
This network shows the impact of papers produced by Daniel Merl. 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 Merl. The network helps show where Daniel Merl may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Merl, 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 | 2010 | 107 | |
| 2 | 2010 | 93 | |
| 3 | 2013 | 60 | |
| 4 | 2009 | 33 | |
| 5 | 2009 | 19 | |
| 6 | 2008 | 7 | |
| 7 | In-Vitro to In-Vivo Factor Profiling in Expression Genomics | 2008 | 5 |
| 8 | 2018 | 4 | |
| 9 | 2021 | 3 | |
| 10 | 2012 | 2 | |
| 11 | amei: An R Package for the Adaptive Management of Epidemiological Interventions | 2010 | 2 |
| 12 | 2025 | 0 | |
| 13 | 2016 | 0 | |
| 14 | 2023 | 0 |
About Daniel Merl
Daniel Merl is a scholar working on Modeling and Simulation, Astronomy and Astrophysics, Epidemiology, Genetics and Applied Mathematics, having authored 14 papers that have together received 335 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (3 papers), Magnetic Field Sensors Techniques (2 papers), Electric Motor Design and Analysis (2 papers), Sensorless Control of Electric Motors (2 papers), Evolution and Genetic Dynamics (2 papers), COVID-19 epidemiological studies (2 papers), Bayesian Methods and Mixture Models (2 papers) and Data Management and Algorithms (1 paper). The work is most often cited by research in Modeling and Simulation (25 citations), Cancer Research (50 citations), Computer Networks and Communications (53 citations), Statistics and Probability (14 citations) and Information Systems (37 citations). Daniel Merl has collaborated with scholars based in United States, Germany and Taiwan. Frequent co-authors include Marc Mangel, Leah R. Johnson, Robert B. Gramacy, Mike West, Jen‐Tsan Chi, Donald E. Ayer, Hanwei Yin, Julia Ling-Yu Chen, Christopher W. Peterson and Deborah M. Muoio. Their work appears in journals such as Journal of Statistical Software, Bayesian Analysis, Computational Statistics & Data Analysis, PLoS Genetics and Journal of the American Statistical Association.
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.