Michael R. Koelle
- Molecular Biology top 5%
- Aging top 0.05%
- Cellular and Molecular Neuroscience top 1%
- Endocrine and Autonomic Systems top 0.5%
- Genetics top 5%
- Co-authors
- H. Robert HorvitzDaniel L. ChaseDavid S. HognessWilliam A. SegravesMichael BenderWilliam S. TalbotPeter CherbasGeorgia A. Patikoglou
- Topics
- Genetics, Aging, and Longevity in Model Organisms (36 papers)Circadian rhythm and melatonin (26 papers)Protein Kinase Regulation and GTPase Signaling (8 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Michael R. Koelle
44 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 99
- Molecular Biology 1.6k
- Aging 1.3k
- Cellular and Molecular Neuroscience 1.2k
- Endocrine and Autonomic Systems 927
- Genetics 402
Countries citing papers authored by Michael R. Koelle
This map shows the geographic impact of Michael R. Koelle'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 Michael R. Koelle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael R. Koelle more than expected).
Fields of papers citing papers by Michael R. Koelle
This network shows the impact of papers produced by Michael R. Koelle. 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 Michael R. Koelle. The network helps show where Michael R. Koelle may publish in the future.
Co-authorship network of co-authors of Michael R. Koelle
This figure shows the co-authorship network connecting the top 25 collaborators of Michael R. Koelle. A scholar is included among the top collaborators of Michael R. Koelle 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 Michael R. Koelle. Michael R. Koelle is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 24 | |
| 4 | 88 | |
| 5 | 29 | |
| 6 | 26 | |
| 7 | 14 | |
| 8 | 50 | |
| 9 | 31 | |
| 10 | 51 | |
| 11 | 44 | |
| 12 | 32 | |
| 13 | 94 | |
| 14 | 234 | |
| 15 | 40 | |
| 16 | 36 | |
| 17 | 159 | |
| 18 | 175 | |
| 19 | EGL-10 Regulates G Protein Signaling in the C. elegans Nervous System and Shares a Conserved Domain with Many Mammalian Proteinsbreakdown → | 497 |
| 20 | The drosophila EcR gene encodes an ecdysone receptor, a new member of the steroid receptor superfamilybreakdown → | 802 |
About Michael R. Koelle
Michael R. Koelle is a scholar working on Aging, Endocrine and Autonomic Systems and Sensory Systems, having authored 44 papers that have together received 3.4k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (36 papers), Circadian rhythm and melatonin (26 papers) and Protein Kinase Regulation and GTPase Signaling (8 papers). The work is most often cited by research in Aging (1.3k citations), Endocrine and Autonomic Systems (927 citations) and Cellular and Molecular Neuroscience (1.2k citations). Michael R. Koelle has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include H. Robert Horvitz, Daniel L. Chase, David S. Hogness, William A. Segraves, Michael Bender, William S. Talbot, Peter Cherbas, Georgia A. Patikoglou, Meng‐Qiu Dong and Kevin M. Collins. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.