Sharon D. Bryant

2.7k total citations
87 papers, 2.2k citations indexed

About

Sharon D. Bryant is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Computational Theory and Mathematics. According to data from OpenAlex, Sharon D. Bryant has authored 87 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Molecular Biology, 65 papers in Cellular and Molecular Neuroscience and 11 papers in Computational Theory and Mathematics. Recurrent topics in Sharon D. Bryant's work include Neuropeptides and Animal Physiology (63 papers), Receptor Mechanisms and Signaling (51 papers) and Pharmacological Receptor Mechanisms and Effects (34 papers). Sharon D. Bryant is often cited by papers focused on Neuropeptides and Animal Physiology (63 papers), Receptor Mechanisms and Signaling (51 papers) and Pharmacological Receptor Mechanisms and Effects (34 papers). Sharon D. Bryant collaborates with scholars based in United States, Italy and Japan. Sharon D. Bryant's co-authors include Severo Salvadori, Lawrence H. Lazarus, Remo Guerrini, Gianfranco Balboni, Yunden Jinsmaa, Yoshio Okada, Clementina Bianchi, Martti Attila, P. S. Cooper and Yuko Tsuda and has published in prestigious journals such as Journal of the American Chemical Society, SHILAP Revista de lepidopterología and Trends in Neurosciences.

In The Last Decade

Sharon D. Bryant

86 papers receiving 2.1k citations

Peers

Sharon D. Bryant
Giuseppe Ronsisvalle Italy
Marián Castro Spain
Jacob Andersen Denmark
Nigel A. Swain United Kingdom
Richard B. Westkaemper United States
Anette M. Johansson Sweden
Simona Bertoni Italy
Anna Janecka Poland
Simon M. N. Efange United States
Georg Höfner Germany
Giuseppe Ronsisvalle Italy
Sharon D. Bryant
Citations per year, relative to Sharon D. Bryant Sharon D. Bryant (= 1×) peers Giuseppe Ronsisvalle

Countries citing papers authored by Sharon D. Bryant

Since Specialization
Citations

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

Fields of papers citing papers by Sharon D. Bryant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sharon D. Bryant. 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 Sharon D. Bryant. The network helps show where Sharon D. Bryant may publish in the future.

Co-authorship network of co-authors of Sharon D. Bryant

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

All Works

20 of 20 papers shown
1.
Vogel, Florian, Christos Andronis, Thomas Seidel, et al.. (2023). GABAA receptor-mediated seizure liabilities: a mixed-methods screening approach. Cell Biology and Toxicology. 39(6). 2793–2819. 3 indexed citations
2.
Kohlbacher, Stefan M., et al.. (2023). A new set of KNIME nodes implementing the QPhAR algorithm. Molecular Informatics. 42(5). e2200245–e2200245.
3.
Ambrosio, Francesca Alessandra, Antonio Lupia, Federica Moraca, et al.. (2023). Molecular and Structural Aspects of Clinically Relevant Mutations of SARS-CoV-2 RNA-Dependent RNA Polymerase in Remdesivir-Treated Patients. Pharmaceuticals. 16(8). 1143–1143. 2 indexed citations
4.
Tomašič, Tihomir, Asta Zubrienė, Žiga Skok, et al.. (2021). Selective DNA Gyrase Inhibitors: Multi-Target in Silico Profiling with 3D-Pharmacophores. Pharmaceuticals. 14(8). 789–789. 8 indexed citations
5.
Tomašič, Tihomir, et al.. (2020). Discovery of Novel Hsp90 C-Terminal Inhibitors Using 3D-Pharmacophores Derived from Molecular Dynamics Simulations. International Journal of Molecular Sciences. 21(18). 6898–6898. 29 indexed citations
6.
7.
Kellici, Tahsin F., Dimitrios Ntountaniotis, George Liapakis, et al.. (2015). Rational Drug Design Paradigms: The Odyssey for Designing Better Drugs. Combinatorial Chemistry & High Throughput Screening. 18(3). 238–256. 8 indexed citations
8.
Marczak, Ewa D., Yunden Jinsmaa, Tingyou Li, et al.. (2007). [N-Allyl-Dmt1]-Endomorphins Are μ-Opioid Receptor Antagonists Lacking Inverse Agonist Properties. Journal of Pharmacology and Experimental Therapeutics. 323(1). 374–380. 11 indexed citations
9.
Li, Tingyou, Yuko Tsuda, Toshio Yokoi, et al.. (2007). Design and synthesis of opioidmimetics containing 2′,6′-dimethyl-l-tyrosine and a pyrazinone-ring platform. Bioorganic & Medicinal Chemistry Letters. 17(21). 5768–5771. 6 indexed citations
10.
Li, Tingyou, Yoshio Fujita, Yuko Tsuda, et al.. (2005). New series of potent δ-opioid antagonists containing the H-Dmt-Tic-NH-hexyl-NH-R motif. Bioorganic & Medicinal Chemistry Letters. 15(24). 5517–5520. 3 indexed citations
11.
Jinsmaa, Yunden, Yoshio Okada, Yuko Tsuda, et al.. (2004). Novel 2′,6′-Dimethyl-l-Tyrosine-Containing Pyrazinone Opioid Mimetic μ-Agonists with Potent Antinociceptive Activity in Mice. Journal of Pharmacology and Experimental Therapeutics. 309(1). 432–438. 40 indexed citations
12.
Santagada, Vincenzo, Gianfranco Balboni, Giuseppe Caliendo, et al.. (2000). Assessment of substitution in the second pharmacophore of Dmt-Tic analogues. Bioorganic & Medicinal Chemistry Letters. 10(24). 2745–2748. 16 indexed citations
13.
Okada, Yoshio, et al.. (1999). Synthesis of Pyrazinone Ring-Containing Opioid Mimetics and Examination of Their Opioid Receptor-Binding Activity.. Chemical and Pharmaceutical Bulletin. 47(8). 1193–1195. 4 indexed citations
14.
Lazarus, Lawrence H., Sharon D. Bryant, P. S. Cooper, & Severo Salvadori. (1999). What peptides these deltorphins be1Paraphrased from Lucius Annaeus Seneca, “What fools these mortals be,” ca 4BCE–65ACE; Epistles 1, 3.1. Progress in Neurobiology. 57(4). 377–420. 61 indexed citations
15.
Guerrini, Remo, Severo Salvadori, Roberto Tomatis, et al.. (1997). Opioid Diketopiperazines: Synthesis and Activity of a Prototypic Class of Opioid Antagonists. Biological Chemistry. 378(1). 19–29. 32 indexed citations
16.
Capasso, Anna, Remo Guerrini, L. Sorrentino, et al.. (1996). Dmt-Tic-OH, a highly selective and potent δ-opioid dipeptide receptor antagonist after systemic administration in the mouse. Life Sciences. 59(8). PL93–PL98. 21 indexed citations
17.
Lazarus, Lawrence H., Sharon D. Bryant, Severo Salvadori, Martti Attila, & Leslie Sargent Jones. (1996). Opioid infidelity: novel opioid peptides with dual high affinity for δ- and μ-receptors. Trends in Neurosciences. 19(1). 31–35. 25 indexed citations
18.
Balboni, Gianfranco, Severo Salvadori, Ferruccio D’Angeli, et al.. (1995). Single diastereomeric desaminotyrosylalanyl tetra‐ and heptapeptides with opioid antagonistic activity. International journal of peptide & protein research. 45(2). 187–193. 1 indexed citations
19.
Lazarus, L.H., Sharon D. Bryant, Martti Attila, & Severo Salvadori. (1994). Frog skin opioid peptides: a case for environmental mimicry.. Environmental Health Perspectives. 102(8). 648–654. 14 indexed citations
20.
Salvadori, Severo, et al.. (1993). Phe3-substituted analogs of deltorphin C. Spatial conformation and topography of the aromatic ring in peptide recognition by .delta. opioid receptors. Journal of Medicinal Chemistry. 36(24). 3748–3756. 37 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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