Steven M. Reppert
- Endocrine and Autonomic Systems top 0.01%
- Cellular and Molecular Neuroscience top 0.05%
- Physiology top 0.1%
- Plant Science top 0.1%
- Cognitive Neuroscience top 0.2%
- Co-authors
- David R. WeaverLauren P. ShearmanDavid C. KleinMark J. ZylkaXiaowei JinRobert Y. MooreElizabeth S. MaywoodTakashi Ebisawa
- Topics
- Circadian rhythm and melatonin (121 papers)Neurobiology and Insect Physiology Research (50 papers)Light effects on plants (28 papers)
- Partner nations
- United StatesUnited KingdomCzechia
In The Last Decade
Steven M. Reppert
163 papers receiving 29.4k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Endocrine and Autonomic Systems 22.8k
- Cellular and Molecular Neuroscience 9.6k
- Physiology 7.2k
- Plant Science 6.1k
- Cognitive Neuroscience 4.4k
Countries citing papers authored by Steven M. Reppert
This map shows the geographic impact of Steven M. Reppert'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 Steven M. Reppert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven M. Reppert more than expected).
Fields of papers citing papers by Steven M. Reppert
This network shows the impact of papers produced by Steven M. Reppert. 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 Steven M. Reppert. The network helps show where Steven M. Reppert may publish in the future.
Co-authorship network of co-authors of Steven M. Reppert
This figure shows the co-authorship network connecting the top 25 collaborators of Steven M. Reppert. A scholar is included among the top collaborators of Steven M. Reppert 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 Steven M. Reppert. Steven M. Reppert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 4 | |
| 3 | 117 | |
| 4 | 53 | |
| 5 | 79 | |
| 6 | 137 | |
| 7 | 367 | |
| 8 | 301 | |
| 9 | 82 | |
| 10 | 338 | |
| 11 | Molecular Analysis of Mammalian Circadian Rhythmsbreakdown → | 1205 |
| 12 | 275 | |
| 13 | A Molecular Mechanism Regulating Rhythmic Output from the Suprachiasmatic Circadian Clockbreakdown → | 764 |
| 14 | 21 | |
| 15 | 50 | |
| 16 | 83 | |
| 17 | Cloning and characterization of a mammalian melatonin receptor that mediates reproductive and circadian responsesbreakdown → | 935 |
| 18 | Suprachiasmatic nucleus : the mind's clockbreakdown → | 1445 |
| 19 | 58 | |
| 20 | 12 |
About Steven M. Reppert
Steven M. Reppert is a scholar working on Endocrine and Autonomic Systems, Aging and Cellular and Molecular Neuroscience, having authored 163 papers that have together received 30.1k indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (121 papers), Neurobiology and Insect Physiology Research (50 papers) and Light effects on plants (28 papers). The work is most often cited by research in Endocrine and Autonomic Systems (22.8k citations), Aging (3.1k citations) and Cellular and Molecular Neuroscience (9.6k citations). Steven M. Reppert has collaborated with scholars based in United States, United Kingdom and Czechia. Frequent co-authors include David R. Weaver, Lauren P. Shearman, David C. Klein, Mark J. Zylka, Xiaowei Jin, Robert Y. Moore, Elizabeth S. Maywood, Takashi Ebisawa, Choogon Lee and Michael H. Hastings. Their work appears in journals such as Nature, Science and Cell.
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.