Jennifer Pons

1.2k citations
14 papers · 745 indexed · h-index 13
Topics
Neuropeptides and Animal Physiology (9 papers)Peptidase Inhibition and Analysis (5 papers)Receptor Mechanisms and Signaling (3 papers)
Partner nations
United States

In The Last Decade

Jennifer Pons

14 papers receiving 732 citations

Peers

Jennifer Pons
Comparison fields: 5 of 94
  • Molecular Biology 283
  • Cellular and Molecular Neuroscience 279
  • Surgery 196
  • Oncology 118
  • Genetics 89
Replace Vincenzo Benagiano with:
Vincenzo Benagiano Italy
Hilary P. Benton United States
B. Cuevas Spain
Bradley Pawlikowski United States
Jin‐Hong Shin South Korea
S. Lindemann Germany
Francesca Wannenes Italy
Philip Catalá-Lehnen Germany
Hannah G. Radley‐Crabb Australia
Pik‐to Cheung Hong Kong
Jennifer Pons relative to Vincenzo Benagiano Italy Vincenzo Benagiano's profile →
Citations per field
00.5×1.5×
Vincenzo Benagiano · 1×
Citations per year

Countries citing papers authored by Jennifer Pons

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer Pons

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jennifer Pons

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 15
2 76
3 46
4 39
5 112
6 30
7 39
8 2
9 20
10 112
11
Neuropeptide Y: multiple receptors and multiple roles in cardiovascular diseases.
38
12 62
13 108
14 46

About Jennifer Pons

Jennifer Pons is a scholar working on Cellular and Molecular Neuroscience, Internal Medicine and Genetics, having authored 14 papers that have together received 745 indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (9 papers), Peptidase Inhibition and Analysis (5 papers) and Receptor Mechanisms and Signaling (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (279 citations), Genetics (89 citations) and Endocrine and Autonomic Systems (56 citations). Jennifer Pons has collaborated with scholars based in United States. Frequent co-authors include Edward Lee, Zofia Żukowska, Joanna Kitlińska, Lijun Li, William Grossman, Hua Su, Junya Takagawa, Janice Arakawa‐Hoyt, Yu Huang and Jianqin Ye. Their work appears in journals such as PLoS ONE, Cancer Research and Biochemical and Biophysical Research Communications.

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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