K Raynor
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- Neuropeptides and Animal Physiology 13
- Molecular Biology top 5%
- Receptor Mechanisms and Signaling 24
- Pharmacological Receptor Mechanisms and Effects 4
- Chemical Synthesis and Analysis 3
- Protein Kinase Regulation and GTPase Signaling 2
- Epidemiology top 5%
- Neuroendocrine Tumor Research Advances 16
- Endocrine and Autonomic Systems top 10%
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- Monoclonal and Polyclonal Antibodies Research 7
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- Cancer, Stress, Anesthesia, and Immune Response 3
- Journals
- Molecular Pharmacology (7 papers)Journal of Pharmacology and Experimental Therapeutics (6 papers)Regulatory Peptides (5 papers)
- Partner nations
- United States
In The Last Decade
K Raynor
31 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Cellular and Molecular Neuroscience 1.6k
- Molecular Biology 1.9k
- Epidemiology 564
- Endocrinology, Diabetes and Metabolism 230
- Endocrine and Autonomic Systems 88
Countries citing papers authored by K Raynor
This map shows the geographic impact of K Raynor'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 K Raynor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K Raynor more than expected).
Fields of papers citing papers by K Raynor
This network shows the impact of papers produced by K Raynor. 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 K Raynor. The network helps show where K Raynor may publish in the future.
Co-authorship network
The 25 scholars most cited alongside K Raynor, 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 | 2007 | 11 | |
| 2 | 2007 | 6 | |
| 3 | 1995 | 65 | |
| 4 | 1994 | 104 | |
| 5 | Pharmacological characterization of the cloned kappa-, delta-, and mu-opioid receptors.breakdown → | 1994 | 571 |
| 6 | 1994 | 7 | |
| 7 | 1994 | 65 | |
| 8 | 1994 | 5 | |
| 9 | 1993 | 9 | |
| 10 | 1993 | 244 | |
| 11 | 1993 | 144 | |
| 12 | 1993 | 56 | |
| 13 | 1993 | 59 | |
| 14 | 1992 | 24 | |
| 15 | 1992 | 25 | |
| 16 | 1991 | 102 | |
| 17 | 1991 | 41 | |
| 18 | 1990 | 108 | |
| 19 | 1990 | 5 | |
| 20 | 1989 | 90 |
About K Raynor
K Raynor is a scholar working on Cellular and Molecular Neuroscience, Epidemiology, Molecular Biology, Radiology, Nuclear Medicine and Imaging and Psychiatry and Mental health, having authored 31 papers that have together received 2.6k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (24 papers), Neuroendocrine Tumor Research Advances (16 papers), Neuropeptides and Animal Physiology (13 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Pharmacological Receptor Mechanisms and Effects (4 papers), Chemical Synthesis and Analysis (3 papers), Cancer, Stress, Anesthesia, and Immune Response (3 papers) and Protein Kinase Regulation and GTPase Signaling (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.6k citations), Molecular Biology (1.9k citations), Epidemiology (564 citations), Endocrinology, Diabetes and Metabolism (230 citations) and Endocrine and Autonomic Systems (88 citations). K Raynor has collaborated with scholars based in United States. Frequent co-authors include Terry Reisine, Hyesik Kong, Graeme I. Bell, Kazuki Yasuda, Jun Takeda, Yong Chen, Lei Yu, G I Bell, Christopher D. Breder and Kei Yasuda. Their work appears in journals such as Molecular Pharmacology, Journal of Pharmacology and Experimental Therapeutics, Regulatory Peptides, Novartis Foundation symposium 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.