Dawn M. Wong

2.1k citations
40 papers · 1.7k indexed · h-index 22
Topics
Cholinesterase and Neurodegenerative Diseases (17 papers)Computational Drug Discovery Methods (10 papers)Neuroscience and Neuropharmacology Research (7 papers)

In The Last Decade

Dawn M. Wong

40 papers receiving 1.6k citations

Peers

Dawn M. Wong
Comparison fields: 5 of 107
  • Pharmacology 745
  • Molecular Biology 579
  • Cellular and Molecular Neuroscience 441
  • Computational Theory and Mathematics 406
  • Organic Chemistry 378
Replace Gabriella Marucci with:
Gabriella Marucci Italy
Catia Lambertucci Italy
Michael O. Chaney United States
Michela Buccioni Italy
Carla Caccia Italy
Marcin Kołaczkowski Poland
Kinga Sałat Poland
Agnieszka A. Kaczor Poland
Tomas de Paulis United States
Federico Dajas Uruguay
Dawn M. Wong relative to Gabriella Marucci Italy Gabriella Marucci's profile →
Citations per field
00.5×1.5×
Gabriella Marucci · 1×
Citations per year

Countries citing papers authored by Dawn M. Wong

Since Specialization
Citations

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

Fields of papers citing papers by Dawn M. Wong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dawn M. Wong. 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 Dawn M. Wong. The network helps show where Dawn M. Wong may publish in the future.

Co-authorship network of co-authors of Dawn M. Wong

This figure shows the co-authorship network connecting the top 25 collaborators of Dawn M. Wong. A scholar is included among the top collaborators of Dawn M. Wong 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 Dawn M. Wong. Dawn M. Wong 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
#WorkIndexed citations
1 6
2 4
3 7
4 31
5 43
6 20
7 29
8 41
9 16
10 54
11 44
12 47
13 37
14 12
15 32
16 27
17 17
18 7
19 18
20 36

About Dawn M. Wong

Dawn M. Wong is a scholar working on Pharmacology, Pharmaceutical Science and Computational Theory and Mathematics, having authored 40 papers that have together received 1.7k indexed citations. Recurring topics across this work include Cholinesterase and Neurodegenerative Diseases (17 papers), Computational Drug Discovery Methods (10 papers) and Neuroscience and Neuropharmacology Research (7 papers). The work is most often cited by research in Pharmacology (745 citations), Computational Theory and Mathematics (406 citations) and Cellular and Molecular Neuroscience (441 citations). Dawn M. Wong has collaborated with scholars based in United States, Israel and Hong Kong. Frequent co-authors include Frank P. Bymaster, Bryan B. Molloy, Jong S. Horng, Ray W. Fuller, Joel L. Sussman, Israel Silman, Paul R. Carlier, Yuan‐Ping Pang, Harry M. Greenblatt and Hay Dvir. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and PLoS ONE.

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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