Lisa Selbie

2.8k citations
35 papers · 2.3k · h-index 17

Impact in

Papers in

Lisa Selbie

33 papers receiving 2.2k citations

Peers

Lisa Selbie
Comparison fields: 5 of 90
  • Physiology 301
  • Cellular and Molecular Neuroscience 1.0k
  • Endocrine and Autonomic Systems 203
  • Molecular Biology 1.3k
  • Sensory Systems 54
Replace Christian Nanoff with:
Christian Nanoff Austria
Ch. Owman Sweden
Stuart J. Mundell United Kingdom
Yigal H. Ehrlich United States
Madan M. Kwatra United States
Daniela Merlo Italy
Ulla E. Petäjä‐Repo Finland
Andreas Breit Germany
Jean‐Pierre Vilardaga United States
Naoto Hoshi Japan
Lisa Selbie relative to Christian Nanoff Austria Christian Nanoff's profile →
Citations per field
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Christian Nanoff · 1×
Citations per year

Countries citing papers authored by Lisa Selbie

Since Specialization
Citations

This map shows the geographic impact of Lisa Selbie'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 Lisa Selbie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lisa Selbie more than expected).

Fields of papers citing papers by Lisa Selbie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lisa Selbie. 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 Lisa Selbie. The network helps show where Lisa Selbie may publish in the future.

Co-authors

The 25 scholars most cited alongside Lisa Selbie, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lisa Selbie Line = papers co-authored together Lisa Selbie links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992363
2 1993302
3 1998266
4 2018227
5 1992167
6 1992134
7 1992122
8 199385
9 198979
10 199367
11 199361
12 199455
13 199544
14 199240
15 199839
16 199231
17 199429
18 199316
19 199816
20 201915

About Lisa Selbie

Lisa Selbie is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Pulmonary and Respiratory Medicine, Psychiatry and Mental health and Radiology, Nuclear Medicine and Imaging, having authored 35 papers that have together received 2.3k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (20 papers), Neuropeptides and Animal Physiology (17 papers), Protein Kinase Regulation and GTPase Signaling (4 papers), Chemical Synthesis and Analysis (4 papers), Effects of Radiation Exposure (3 papers), Adenosine and Purinergic Signaling (2 papers), Bipolar Disorder and Treatment (2 papers) and Ion channel regulation and function (2 papers). The work is most often cited by research in Physiology (301 citations), Cellular and Molecular Neuroscience (1.0k citations), Endocrine and Autonomic Systems (203 citations), Molecular Biology (1.3k citations) and Sensory Systems (54 citations). Lisa Selbie has collaborated with scholars based in Australia, United Kingdom and New Zealand. Frequent co-authors include John Shine, Stephen J. Hill, Gillian R. Hayes, Herbert Herzog, Trevor J. Biden, Carsten Schmitz‐Peiffer, Timothy J. Furlong, Kerrie D. Pierce, Helen J. Ball and Yvonne Hort. Their work appears in journals such as Journal of Affective Disorders, Journal of Biological Chemistry, Biochemical and Biophysical Research Communications, British Journal of Pharmacology 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.

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