Alexander S. Hauser
- Molecular Biology top 2%
- Cellular and Molecular Neuroscience top 0.5%
- Radiology, Nuclear Medicine and Imaging top 2%
- Computational Theory and Mathematics top 0.5%
- Spectroscopy top 5%
- Co-authors
- David E. GloriamHelgi B. SchiöthMathias Rask‐AndersenMisty M. AttwoodChristian MunkKasper HarpsøeStefan MordalskiAndrzej J. Bojarski
- Topics
- Receptor Mechanisms and Signaling (37 papers)Neuropeptides and Animal Physiology (19 papers)Computational Drug Discovery Methods (8 papers)
- Journals
- NatureCellNucleic Acids Research
- Partner nations
- DenmarkUnited StatesUnited Kingdom
In The Last Decade
Alexander S. Hauser
47 papers receiving 4.5k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Molecular Biology 3.8k
- Cellular and Molecular Neuroscience 1.9k
- Radiology, Nuclear Medicine and Imaging 675
- Computational Theory and Mathematics 637
- Spectroscopy 317
Countries citing papers authored by Alexander S. Hauser
This map shows the geographic impact of Alexander S. Hauser'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 Alexander S. Hauser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander S. Hauser more than expected).
Fields of papers citing papers by Alexander S. Hauser
This network shows the impact of papers produced by Alexander S. Hauser. 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 Alexander S. Hauser. The network helps show where Alexander S. Hauser may publish in the future.
Co-authorship network of co-authors of Alexander S. Hauser
This figure shows the co-authorship network connecting the top 25 collaborators of Alexander S. Hauser. A scholar is included among the top collaborators of Alexander S. Hauser 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 Alexander S. Hauser. Alexander S. Hauser 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 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | GPCR drug discovery: new agents, targets and indicationsbreakdown → | 31 |
| 6 | 1 | |
| 7 | 10 | |
| 8 | 23 | |
| 9 | 20 | |
| 10 | 8 | |
| 11 | 2 | |
| 12 | Effector membrane translocation biosensors reveal G protein and βarrestin coupling profiles of 100 therapeutically relevant GPCRsbreakdown → | 145 |
| 13 | 22 | |
| 14 | 16 | |
| 15 | 176 | |
| 16 | 8 | |
| 17 | 278 | |
| 18 | 151 | |
| 19 | 35 | |
| 20 | 365 |
About Alexander S. Hauser
Alexander S. Hauser is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Pharmacology, having authored 49 papers that have together received 4.5k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (37 papers), Neuropeptides and Animal Physiology (19 papers) and Computational Drug Discovery Methods (8 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.9k citations), Molecular Biology (3.8k citations) and Computational Theory and Mathematics (637 citations). Alexander S. Hauser has collaborated with scholars based in Denmark, United States and United Kingdom. Frequent co-authors include David E. Gloriam, Helgi B. Schiöth, Mathias Rask‐Andersen, Misty M. Attwood, Christian Munk, Kasper Harpsøe, Stefan Mordalski, Andrzej J. Bojarski, Vignir Ísberg and M. Madan Babu. Their work appears in journals such as Nature, Cell and Nucleic Acids Research.
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.