Janice Shaw

877 total citations
15 papers, 739 citations indexed

About

Janice Shaw is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Endocrine and Autonomic Systems. According to data from OpenAlex, Janice Shaw has authored 15 papers receiving a total of 739 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cellular and Molecular Neuroscience, 6 papers in Molecular Biology and 5 papers in Endocrine and Autonomic Systems. Recurrent topics in Janice Shaw's work include Neurotransmitter Receptor Influence on Behavior (6 papers), Regulation of Appetite and Obesity (5 papers) and Receptor Mechanisms and Signaling (4 papers). Janice Shaw is often cited by papers focused on Neurotransmitter Receptor Influence on Behavior (6 papers), Regulation of Appetite and Obesity (5 papers) and Receptor Mechanisms and Signaling (4 papers). Janice Shaw collaborates with scholars based in United States. Janice Shaw's co-authors include Donald R. Gehlert, Eyassu Chernet, Wei Zhang, Frank P. Bymaster, David T. Wong, Kenneth W. Perry, Lee A. Phebus, Todd J. Kohn, Tammy J. Sajdyk and Mark Wade and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Neuroscience and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Janice Shaw

15 papers receiving 721 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Janice Shaw United States 12 293 216 149 142 131 15 739
Angelo Blasio United States 16 403 1.4× 227 1.1× 181 1.2× 195 1.4× 240 1.8× 22 938
Mike Bickerdike United Kingdom 10 492 1.7× 283 1.3× 81 0.5× 62 0.4× 109 0.8× 15 741
Philip Gerrard United Kingdom 17 643 2.2× 418 1.9× 106 0.7× 144 1.0× 134 1.0× 19 1.1k
Ida Fredriksson United States 15 565 1.9× 203 0.9× 162 1.1× 80 0.6× 201 1.5× 22 878
Ruggero Galici United States 16 700 2.4× 488 2.3× 210 1.4× 86 0.6× 121 0.9× 24 1.1k
David S. Janowsky United States 13 284 1.0× 172 0.8× 123 0.8× 205 1.4× 53 0.4× 23 690
Ilga Misane Sweden 17 622 2.1× 394 1.8× 104 0.7× 145 1.0× 78 0.6× 21 945
David J. Barber United Kingdom 17 446 1.5× 245 1.1× 148 1.0× 68 0.5× 66 0.5× 33 773
Chung Sub Kim United States 10 265 0.9× 212 1.0× 374 2.5× 231 1.6× 58 0.4× 12 933
Lotte de Groote Germany 14 386 1.3× 227 1.1× 100 0.7× 339 2.4× 82 0.6× 18 846

Countries citing papers authored by Janice Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Janice Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Janice Shaw

This figure shows the co-authorship network connecting the top 25 collaborators of Janice Shaw. A scholar is included among the top collaborators of Janice Shaw 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 Janice Shaw. Janice Shaw is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Cabrera, Over, James Ficorilli, Janice Shaw, et al.. (2021). Intra-islet glucagon confers β-cell glucose competence for first-phase insulin secretion and favors GLP-1R stimulation by exogenous glucagon. Journal of Biological Chemistry. 298(2). 101484–101484. 23 indexed citations
2.
Gehlert, Donald R. & Janice Shaw. (2014). 5-Hydroxytryptamine 1A (5HT1A) receptors mediate increases in plasma glucose independent of corticosterone. European Journal of Pharmacology. 745. 91–97. 8 indexed citations
3.
Shaw, Janice, et al.. (2013). 5-HT1A receptor antagonists reduce food intake and body weight by reducing total meals with no conditioned taste aversion. Pharmacology Biochemistry and Behavior. 112. 1–8. 25 indexed citations
4.
Sindelar, Dana K., Michelle Morin, Janice Shaw, et al.. (2013). LLY-2707, A Novel Nonsteroidal Glucocorticoid Antagonist That Reduces Atypical Antipsychotic–Associated Weight Gain in Rats. Journal of Pharmacology and Experimental Therapeutics. 348(1). 192–201. 7 indexed citations
5.
McNair, Lisa, et al.. (2011). WEMSS report: A clinical, economic and operational evaluation of pilot women's enhanced medium secure services (WEMSS). Research Explorer (The University of Manchester). 3 indexed citations
6.
Gehlert, Donald R., Kurt Rasmussen, Janice Shaw, et al.. (2009). Preclinical Evaluation of Melanin-Concentrating Hormone Receptor 1 Antagonism for the Treatment of Obesity and Depression. Journal of Pharmacology and Experimental Therapeutics. 329(2). 429–438. 62 indexed citations
7.
Gehlert, Donald R., Linda Thompson, Susan K. Hemrick-Luecke, & Janice Shaw. (2008). Monoaminergic compensation in the neuropeptide Y deficient mouse brain. Neuropeptides. 42(3). 367–375. 17 indexed citations
8.
Gehlert, Donald R., Anantha Shekhar, Stéphanie Morin, et al.. (2005). Stress and central Urocortin increase anxiety-like behavior in the social interaction test via the CRF1 receptor. European Journal of Pharmacology. 509(2-3). 145–153. 89 indexed citations
9.
Takeuchi, Kumiko, Todd J. Kohn, Vincent P. Rocco, et al.. (2005). Advances toward new antidepressants beyond SSRIs: 1-Aryloxy-3-piperidinylpropan-2-ols with dual 5-HT1A receptor antagonism/SSRI activities. Part 5. Bioorganic & Medicinal Chemistry Letters. 16(9). 2347–2351. 17 indexed citations
10.
Smith, Daniel G., Eleni T. Tzavara, Janice Shaw, et al.. (2005). Mesolimbic Dopamine Super-Sensitivity in Melanin-Concentrating Hormone-1 Receptor-Deficient Mice. Journal of Neuroscience. 25(4). 914–922. 93 indexed citations
11.
Rocco, Vincent P., Todd J. Kohn, David L. Nelson, et al.. (2004). Advances toward new antidepressants beyond SSRIs: 1-aryloxy-3-piperidinylpropan-2-ols with dual 5-HT1A receptor antagonism/SSRI activities. Part 4. Bioorganic & Medicinal Chemistry Letters. 14(10). 2653–2656. 30 indexed citations
12.
Takeuchi, Kumiko, Todd J. Kohn, Vincent P. Rocco, et al.. (2003). Advances toward new antidepressants beyond SSRIs: 1-aryloxy-3-piperidinylpropan-2-ols with dual 5-HT1A receptor antagonism/SSRI activities. Part 3. Bioorganic & Medicinal Chemistry Letters. 13(22). 3939–3942. 18 indexed citations
13.
Takeuchi, Kumiko, Todd J. Kohn, Vincent P. Rocco, et al.. (2003). Advances toward new antidepressants beyond SSRIs: 1-aryloxy-3-piperidinylpropan-2-ols with dual 5-HT1A receptor antagonism/SSRI activities. Part 1. Bioorganic & Medicinal Chemistry Letters. 13(11). 1903–1905. 45 indexed citations
14.
Takeuchi, Kumiko, Todd J. Kohn, Vincent P. Rocco, et al.. (2003). Advances Toward new antidepressants beyond SSRIs: 1-aryloxy-3-piperidinylpropan-2-ols with dual 5-HT1A receptor antagonism/SSRI activities. Part 2. Bioorganic & Medicinal Chemistry Letters. 13(14). 2393–2397. 20 indexed citations
15.
Bymaster, Frank P., Wei Zhang, Janice Shaw, et al.. (2002). Fluoxetine, but not other selective serotonin uptake inhibitors, increases norepinephrine and dopamine extracellular levels in prefrontal cortex. Psychopharmacology. 160(4). 353–361. 282 indexed citations

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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