Ruth M. Seeber
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- Neuropeptides and Animal Physiology 6
- Neurobiology and Insect Physiology Research 4
- Neuroscience and Neuropharmacology Research 2
- Molecular Biology top 10%
- Receptor Mechanisms and Signaling 15
- Endocrine and Autonomic Systems top 10%
- Biophysics top 5%
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- Chemokine receptors and signaling 3
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- Monoclonal and Polyclonal Antibodies Research 3
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- GaN-based semiconductor devices and materials 3
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- Computational Drug Discovery Methods 2
- Co-authors
- Karin A. EidneKevin D. G. PflegerAylin C. HanyalogluKaren M. KroegerHeng B. SeeLauren E.C. MilesJulian J. AdamsWilliam J. McKinstry
- Journals
- Journal of Biological Chemistry (5 papers)Journal of Clinical Investigation (1 paper)PLoS ONE (2 papers)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Ruth M. Seeber
25 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 96
- Cellular and Molecular Neuroscience 329
- Molecular Biology 911
- Endocrinology, Diabetes and Metabolism 215
- Endocrine and Autonomic Systems 84
- Biophysics 56
Countries citing papers authored by Ruth M. Seeber
This map shows the geographic impact of Ruth M. Seeber'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 Ruth M. Seeber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruth M. Seeber more than expected).
Fields of papers citing papers by Ruth M. Seeber
This network shows the impact of papers produced by Ruth M. Seeber. 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 Ruth M. Seeber. The network helps show where Ruth M. Seeber may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ruth M. Seeber, 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 | 2022 | 6 | |
| 2 | 2021 | 4 | |
| 3 | 2018 | 67 | |
| 4 | 2013 | 23 | |
| 5 | 2013 | 14 | |
| 6 | 2012 | 48 | |
| 7 | 2012 | 10 | |
| 8 | 2012 | 57 | |
| 9 | 2011 | 61 | |
| 10 | 2010 | 45 | |
| 11 | 2010 | 2 | |
| 12 | 2008 | 38 | |
| 13 | 2008 | 72 | |
| 14 | 2008 | 75 | |
| 15 | 2006 | 170 | |
| 16 | 2006 | 1 | |
| 17 | 2005 | 293 | |
| 18 | 2004 | 86 | |
| 19 | 2002 | 68 | |
| 20 | 2002 | 58 |
About Ruth M. Seeber
Ruth M. Seeber is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Condensed Matter Physics, having authored 26 papers that have together received 1.4k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (15 papers), Neuropeptides and Animal Physiology (6 papers), Neurobiology and Insect Physiology Research (4 papers), Chemokine receptors and signaling (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), GaN-based semiconductor devices and materials (3 papers), Neuroscience and Neuropharmacology Research (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (329 citations), Molecular Biology (911 citations) and Endocrinology, Diabetes and Metabolism (215 citations). Ruth M. Seeber has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Karin A. Eidne, Kevin D. G. Pfleger, Aylin C. Hanyaloglu, Karen M. Kroeger, Heng B. See, Lauren E.C. Miles, Julian J. Adams, William J. McKinstry, Michael W. Parker and Rebecca Pelekanos. Their work appears in journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and PLoS ONE.
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.