Daniel B. Rubin
- Statistics and Probability top 0.5%
- Oncology top 5%
- Cognitive Neuroscience top 5%
- Cellular and Molecular Neuroscience top 5%
- Molecular Biology
- Co-authors
- Mark J. van der LaanKenneth D. MillerStephen D. Van HooserMichael J. CaplanKai DuMarie E. EganScott A. WeinerJudith Glöckner-Pagel
- Topics
- Statistical Methods and Inference (13 papers)Statistical Methods in Clinical Trials (11 papers)Statistical Methods and Bayesian Inference (11 papers)
- Partner nations
- United StatesItalyIsrael
In The Last Decade
Daniel B. Rubin
93 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 174
- Statistics and Probability 665
- Oncology 497
- Cognitive Neuroscience 481
- Cellular and Molecular Neuroscience 421
- Molecular Biology 402
Countries citing papers authored by Daniel B. Rubin
This map shows the geographic impact of Daniel B. Rubin'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 B. Rubin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel B. Rubin more than expected).
Fields of papers citing papers by Daniel B. Rubin
This network shows the impact of papers produced by Daniel B. Rubin. 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 B. Rubin. The network helps show where Daniel B. Rubin may publish in the future.
Co-authorship network of co-authors of Daniel B. Rubin
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel B. Rubin. A scholar is included among the top collaborators of Daniel B. Rubin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel B. Rubin. Daniel B. Rubin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 11 | |
| 5 | 0 | |
| 6 | 8 | |
| 7 | 11 | |
| 8 | 4 | |
| 9 | 6 | |
| 10 | 200 | |
| 11 | 59 | |
| 12 | 58 | |
| 13 | 6 | |
| 14 | The Problem of Vaccination Noncompliance: Public Health Goals and the Limitations of Tort Law | 1 |
| 15 | 62 | |
| 16 | 2 | |
| 17 | 3 | |
| 18 | 24 | |
| 19 | 5 | |
| 20 | 23 |
About Daniel B. Rubin
Daniel B. Rubin is a scholar working on Statistics and Probability, Applied Microbiology and Biotechnology and Neurology, having authored 99 papers that have together received 3.6k indexed citations. Recurring topics across this work include Statistical Methods and Inference (13 papers), Statistical Methods in Clinical Trials (11 papers) and Statistical Methods and Bayesian Inference (11 papers). The work is most often cited by research in Statistics and Probability (665 citations), Molecular Medicine (249 citations) and Applied Microbiology and Biotechnology (92 citations). Daniel B. Rubin has collaborated with scholars based in United States, Italy and Israel. Frequent co-authors include Mark J. van der Laan, Kenneth D. Miller, Stephen D. Van Hooser, Michael J. Caplan, Kai Du, Marie E. Egan, Scott A. Weiner, Judith Glöckner-Pagel, Susan Canny and Gergely L. Lukács. Their work appears in journals such as Science, New England Journal of Medicine and Proceedings of the National Academy of Sciences.
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.