Lauren Willard

401 total citations
8 papers, 314 citations indexed

About

Lauren Willard is a scholar working on Cellular and Molecular Neuroscience, Pharmacology and Surgery. According to data from OpenAlex, Lauren Willard has authored 8 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cellular and Molecular Neuroscience, 3 papers in Pharmacology and 2 papers in Surgery. Recurrent topics in Lauren Willard's work include Neuroscience and Neuropharmacology Research (2 papers), Receptor Mechanisms and Signaling (2 papers) and Neuropeptides and Animal Physiology (2 papers). Lauren Willard is often cited by papers focused on Neuroscience and Neuropharmacology Research (2 papers), Receptor Mechanisms and Signaling (2 papers) and Neuropeptides and Animal Physiology (2 papers). Lauren Willard collaborates with scholars based in United States. Lauren Willard's co-authors include Gary L. Wenk, Beatrice Hauss‐Wegrzyniak, Wojciech Danysz, Michael P. McDonald, Jacqueline N. Crawley, Piero Del Soldato, Giancarlo Pepeu, John S. Markowitz, S. Craig Risch and C. Lindsay DeVane and has published in prestigious journals such as Journal of Neuroscience, Brain Research and Experimental Brain Research.

In The Last Decade

Lauren Willard

8 papers receiving 301 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lauren Willard United States 5 130 115 104 98 60 8 314
Jolanta Pupure Latvia 13 102 0.8× 225 2.0× 85 0.8× 100 1.0× 43 0.7× 19 451
Agnieszka Falinska United Kingdom 6 95 0.7× 113 1.0× 121 1.2× 215 2.2× 69 1.1× 9 367
Michael Hilgert Germany 6 102 0.8× 169 1.5× 80 0.8× 96 1.0× 52 0.9× 8 376
Ahmed S. Kamel Egypt 10 111 0.9× 149 1.3× 56 0.5× 70 0.7× 56 0.9× 31 416
Debora Fazzi Italy 6 100 0.8× 96 0.8× 82 0.8× 77 0.8× 58 1.0× 6 300
Duy-Khanh Dang South Korea 13 119 0.9× 126 1.1× 106 1.0× 51 0.5× 37 0.6× 13 388
Nida Jamali-Raeufy Iran 11 139 1.1× 102 0.9× 69 0.7× 62 0.6× 60 1.0× 21 394
Zhuoyou Chen China 9 158 1.2× 190 1.7× 69 0.7× 83 0.8× 85 1.4× 14 431
Ahsan Habib United States 9 67 0.5× 105 0.9× 54 0.5× 202 2.1× 55 0.9× 20 326
Smijin Soman India 13 126 1.0× 157 1.4× 56 0.5× 98 1.0× 40 0.7× 19 419

Countries citing papers authored by Lauren Willard

Since Specialization
Citations

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

Fields of papers citing papers by Lauren Willard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lauren Willard

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

All Works

8 of 8 papers shown
1.
Harvey, P., et al.. (2022). PSAT032 Metoclopramide Induced Pheochromocytoma Multisystem Crisis: An Unusual Initial Presentation of Pheochromocytoma. Journal of the Endocrine Society. 6(Supplement_1). A102–A102. 1 indexed citations
2.
DeVane, C. Lindsay, Jennifer L. Donovan, Heidi L. Liston, et al.. (2004). Comparative CYP3A4 Inhibitory Effects of Venlafaxine, Fluoxetine, Sertraline, and Nefazodone in Healthy Volunteers. Journal of Clinical Psychopharmacology. 24(1). 4–10. 46 indexed citations
3.
Nemeroff, Charles B., A.R. Entsuah, Lauren Willard, Mark A. Demitrack, & M.E. Thase. (2003). P.1.189 Venlafaxine and SSRIs: Pooled remission analysis. European Neuropsychopharmacology. 13. S255–S255. 2 indexed citations
4.
Liston, Heidi L., et al.. (2002). Lack of venlafaxine CYP3A4 inhibitory effects on oral and IV model substrates. European Neuropsychopharmacology. 12. 229–230. 1 indexed citations
5.
Willard, Lauren, Beatrice Hauss‐Wegrzyniak, Wojciech Danysz, & Gary L. Wenk. (2000). The cytotoxicity of chronic neuroinflammation upon basal forebrain cholinergic neurons of rats can be attenuated by glutamatergic antagonism or cyclooxygenase-2 inhibition. Experimental Brain Research. 134(1). 58–65. 104 indexed citations
6.
Hauss‐Wegrzyniak, Beatrice, Lauren Willard, Piero Del Soldato, Giancarlo Pepeu, & Gary L. Wenk. (1999). Peripheral administration of novel anti-inflammatories can attenuate the effects of chronic inflammation within the CNS. Brain Research. 815(1). 36–43. 61 indexed citations
7.
Wenk, Gary L. & Lauren Willard. (1998). The neural mechanisms underlying cholinergic celldeath within the basal FOREBRAIN. International Journal of Developmental Neuroscience. 16(7-8). 729–735. 47 indexed citations
8.
McDonald, Michael P., Lauren Willard, Gary L. Wenk, & Jacqueline N. Crawley. (1998). Coadministration of Galanin Antagonist M40 with a Muscarinic M1Agonist Improves Delayed Nonmatching to Position Choice Accuracy in Rats with Cholinergic Lesions. Journal of Neuroscience. 18(13). 5078–5085. 52 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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