Danette Pascarella

916 total citations
6 papers, 528 citations indexed

About

Danette Pascarella is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Biochemistry. According to data from OpenAlex, Danette Pascarella has authored 6 papers receiving a total of 528 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Cellular and Molecular Neuroscience and 3 papers in Biochemistry. Recurrent topics in Danette Pascarella's work include Neuroscience and Neuropharmacology Research (4 papers), Amino Acid Enzymes and Metabolism (3 papers) and Receptor Mechanisms and Signaling (3 papers). Danette Pascarella is often cited by papers focused on Neuroscience and Neuropharmacology Research (4 papers), Amino Acid Enzymes and Metabolism (3 papers) and Receptor Mechanisms and Signaling (3 papers). Danette Pascarella collaborates with scholars based in United States and United Kingdom. Danette Pascarella's co-authors include Marlene A. Jacobson, Pierre Mallorga, Jacinta B. Williams, Douglas J. Pettibone, Cyrille Sur, Marion Wittmann, Philip E. Brandish, Edward M. Scolnick, P. Jeffrey Conn and Zhizhen Zeng and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Pharmacology and Experimental Therapeutics and Molecular Pharmacology.

In The Last Decade

Danette Pascarella

6 papers receiving 513 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Danette Pascarella United States 6 354 341 118 70 66 6 528
Sarah L. Huszar United States 10 179 0.5× 239 0.7× 69 0.6× 60 0.9× 27 0.4× 12 400
Michael Popiolek United States 12 197 0.6× 245 0.7× 37 0.3× 40 0.6× 69 1.0× 15 398
Shirly Amar Israel 10 224 0.6× 338 1.0× 222 1.9× 155 2.2× 54 0.8× 14 577
Mao Horio Japan 12 259 0.7× 247 0.7× 222 1.9× 198 2.8× 23 0.3× 14 516
Berthold Behl Germany 15 273 0.8× 250 0.7× 54 0.5× 54 0.8× 57 0.9× 25 494
О. К. Савушкина Russia 12 171 0.5× 152 0.4× 69 0.6× 161 2.3× 94 1.4× 59 478
S. Kitayama Japan 12 570 1.6× 455 1.3× 65 0.6× 18 0.3× 19 0.3× 27 772
Alan Sarup Denmark 8 329 0.9× 211 0.6× 36 0.3× 32 0.5× 57 0.9× 8 417
Katarína Lichnerová Czechia 11 346 1.0× 290 0.9× 30 0.3× 42 0.6× 35 0.5× 11 532
Linda M. Pullan United States 15 289 0.8× 382 1.1× 81 0.7× 25 0.4× 37 0.6× 29 609

Countries citing papers authored by Danette Pascarella

Since Specialization
Citations

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

Fields of papers citing papers by Danette Pascarella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danette Pascarella

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

All Works

6 of 6 papers shown
1.
Kutchukian, Peter S., Brian C. Magliaro, Paul Zuck, et al.. (2016). Iterative Focused Screening with Biological Fingerprints Identifies Selective Asc-1 Inhibitors Distinct from Traditional High Throughput Screening. ACS Chemical Biology. 12(2). 519–527. 15 indexed citations
2.
Jacobson, Marlene A., Constantine Kreatsoulas, Danette Pascarella, Julie A. O’Brien, & Cyrille Sur. (2010). The M1 Muscarinic Receptor Allosteric Agonists AC-42 and 1-[1′-(2-Methylbenzyl)-1,4′-bipiperidin-4-yl]-1,3-dihydro-2H-benzimidazol-2-one Bind to a Unique Site Distinct from the Acetylcholine Orthosteric Site. Molecular Pharmacology. 78(4). 648–657. 24 indexed citations
3.
Smith, Sean M., Jason M. Uslaner, Lihang Yao, et al.. (2008). The Behavioral and Neurochemical Effects of a Novel d-Amino Acid Oxidase Inhibitor Compound 8 [4 H-Thieno [3,2-b]pyrrole-5-carboxylic Acid] and d-Serine. Journal of Pharmacology and Experimental Therapeutics. 328(3). 921–930. 73 indexed citations
4.
Sparey, Tim, Pravien Abeywickrema, Sarah Almond, et al.. (2008). The discovery of fused pyrrole carboxylic acids as novel, potent d-amino acid oxidase (DAO) inhibitors. Bioorganic & Medicinal Chemistry Letters. 18(11). 3386–3391. 63 indexed citations
5.
Sur, Cyrille, Pierre Mallorga, Marion Wittmann, et al.. (2003). N-desmethylclozapine, an allosteric agonist at muscarinic 1 receptor, potentiates N-methyl- d -aspartate receptor activity. Proceedings of the National Academy of Sciences. 100(23). 13674–13679. 242 indexed citations
6.
Pettibone, Douglas J., J. Fred Hess, Patricia J. Hey, et al.. (2002). The Effects of Deleting the Mouse Neurotensin Receptor NTR1 on Central and Peripheral Responses to Neurotensin. Journal of Pharmacology and Experimental Therapeutics. 300(1). 305–313. 111 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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