Peter Leeds

3.6k total citations
29 papers, 3.0k citations indexed

About

Peter Leeds is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Genetics. According to data from OpenAlex, Peter Leeds has authored 29 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 11 papers in Cellular and Molecular Neuroscience and 6 papers in Genetics. Recurrent topics in Peter Leeds's work include Histone Deacetylase Inhibitors Research (11 papers), Neuroscience and Neuropharmacology Research (7 papers) and Signaling Pathways in Disease (5 papers). Peter Leeds is often cited by papers focused on Histone Deacetylase Inhibitors Research (11 papers), Neuroscience and Neuropharmacology Research (7 papers) and Signaling Pathways in Disease (5 papers). Peter Leeds collaborates with scholars based in United States, Taiwan and Japan. Peter Leeds's co-authors include De‐Maw Chuang, Yan Leng, De‐Maw Chuang, Ming Ren, Li‐Kai Tsai, Hyeon Ju Kim, Hirohiko Kanai, Zhifei Wang, Ren‐Wu Chen and Zoya Marinova and has published in prestigious journals such as Journal of Neuroscience, Stroke and Scientific Reports.

In The Last Decade

Peter Leeds

29 papers receiving 3.0k citations

Peers

Peter Leeds
Comparison fields: 5 of 114
  • Molecular Biology 1.7k
  • Cellular and Molecular Neuroscience 840
  • Genetics 456
  • Psychiatry and Mental health 449
  • Neurology 376
Replace Chi‐Tso Chiu with:
Chi‐Tso Chiu Taiwan
Ming Ren China
Stefania Ceruti Italy
Hai‐Ying Shen United States
Francesca Biagioni Italy
Jon Nilsen United States
Ana Patricia Fernández Spain
Eitan Friedman United States
Alberto Pérez-Samartı́n Spain
Ming Ren United States
Chi‐Tso Chiu Taiwan View profile →
Citations per field, relative to Peter Leeds
Peter Leeds · 1×
Citations per year, relative to Peter Leeds
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Countries citing papers authored by Peter Leeds

Since Specialization
Citations

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

Fields of papers citing papers by Peter Leeds

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Leeds

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Leeds. A scholar is included among the top collaborators of Peter Leeds 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 Peter Leeds. Peter Leeds 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
# Work Indexed citations
1 39
2 97
3 82
4 99
5 120
6 68
7 204
8 110
9 268
10 187
11 92
12 335
13 42
14 83
15 131
16 203
17 106
18 87
19 97
20 33

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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