Li‐Da Su

615 citations
35 papers · 423 · h-index 13

Impact in

Papers in

Li‐Da Su

33 papers receiving 419 citations

Peers

Li‐Da Su
Comparison fields: 5 of 73
  • Cellular and Molecular Neuroscience 171
  • Neurology 69
  • Developmental Neuroscience 27
  • Endocrine and Autonomic Systems 26
  • Sensory Systems 19
Replace Jean-Louis Molat with:
Jean-Louis Molat France
Raghavendra Y. Nagaraja United States
Yun‐Fang Jia United States
Chiara Betelli Italy
Thomas Lorivel France
Lindsey A. Chew United States
Shaoqiu He United States
Wiebke Fleischer Germany
Zhenjun Tan United States
Xianfu Lu China
Li‐Da Su relative to Jean-Louis Molat France Jean-Louis Molat's profile →
Citations per field
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Jean-Louis Molat · 1×
Citations per year

Countries citing papers authored by Li‐Da Su

Since Specialization
Citations

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

Fields of papers citing papers by Li‐Da Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Li‐Da Su. 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 Li‐Da Su. The network helps show where Li‐Da Su may publish in the future.

Co-authors

The 25 scholars most cited alongside Li‐Da Su, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Li‐Da Su Line = papers co-authored together Li‐Da Su links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201462
2 201333
3 202132
4 201731
5 201029
6 201826
7 202026
8 201019
9 201315
10 200714
11 200914
12 201314
13 201314
14 201312
15 201211
16 20249
17 20187
18 20147
19 20166
20 20156

About Li‐Da Su

Li‐Da Su is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Endocrine and Autonomic Systems, Cognitive Neuroscience and Pharmacology, having authored 35 papers that have together received 423 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (12 papers), Neuroscience of respiration and sleep (5 papers), Cannabis and Cannabinoid Research (4 papers), Genetics and Neurodevelopmental Disorders (4 papers), Ion channel regulation and function (3 papers), Traumatic Brain Injury and Neurovascular Disturbances (2 papers), Retinoids in leukemia and cellular processes (2 papers) and Cellular transport and secretion (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (171 citations), Neurology (69 citations), Developmental Neuroscience (27 citations), Endocrine and Autonomic Systems (26 citations) and Sensory Systems (19 citations). Li‐Da Su has collaborated with scholars based in China, United States and Madagascar. Frequent co-authors include Ying Shen, Chenglong Sun, Lin Zhou, Dong Uk Yang, Dejuan Wang, Yajun Xie, Liang Zhou, Na Wang, Yanan Wang and Junhai Han. Their work appears in journals such as The Cerebellum, PLoS ONE, Journal of Neuroscience, Neuroscience and Nature 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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