Li‐Da Su

598 citations
34 papers · 414 · h-index 13

Impact in

Papers in

Li‐Da Su

32 papers receiving 409 citations

Peers

Li‐Da Su
Comparison fields: 5 of 75
  • Cellular and Molecular Neuroscience 186
  • Neurology 69
  • Developmental Neuroscience 30
  • Endocrine and Autonomic Systems 30
  • Sensory Systems 18
Replace Chalid Ghadban with:
Chalid Ghadban Germany
Thomas Lorivel France
Erika Vázquez‐Juárez Mexico
Wiebke Fleischer Germany
Aiping Xing China
Raghavendra Y. Nagaraja United States
Sin‐Jhong Cheng Taiwan
Sandra Leo Belgium
Mónica E. Ureña‐Guerrero Mexico
P. Lorenzo Bozzelli United States
Li‐Da Su relative to Chalid Ghadban Germany Chalid Ghadban's profile →
Citations per field
00.5×
Chalid Ghadban · 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 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201462
2 201333
3 202131
4 201730
5 201029
6 201825
7 202024
8 201019
9 201315
10 201314
11 201314
12 200714
13 200913
14 201312
15 201211
16 20248
17 20147
18 20187
19 20146
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 34 papers that have together received 414 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (15 papers), Neuroscience of respiration and sleep (7 papers), Cannabis and Cannabinoid Research (4 papers), Ion channel regulation and function (4 papers), Genetics and Neurodevelopmental Disorders (4 papers), Cellular transport and secretion (3 papers), Neonatal and fetal brain pathology (2 papers) and Retinoids in leukemia and cellular processes (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (186 citations), Neurology (69 citations), Developmental Neuroscience (30 citations), Endocrine and Autonomic Systems (30 citations) and Sensory Systems (18 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, Na Wang, Liang Zhou, Yanan Wang and Junhai Han. Their work appears in journals such as The Cerebellum, PLoS ONE, Journal of Neuroscience, Neuroscience and Traffic.

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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