Ya-Lan Sun

1.1k citations
29 papers · 861 · h-index 13

Impact in

Papers in

Ya-Lan Sun

26 papers receiving 841 citations

Peers

Ya-Lan Sun
Comparison fields: 5 of 86
  • Obstetrics and Gynecology 171
  • Insect Science 256
  • Cellular and Molecular Neuroscience 310
  • Geophysics 110
  • Genetics 148
Replace Miriam Harel with:
Miriam Harel Israel
Marıá Gracia Gervasi United States
Linda Lefièvre United Kingdom
J Slavíček Czechia
Victoria Shilova Russia
Gregory S. Kopf United States
D. Janette Tubb United States
Akitsugu Sato Japan
Boris Risek United States
Normann Goodwin Germany
Ya-Lan Sun relative to Miriam Harel Israel Miriam Harel's profile →
Citations per field
00.5×5×10×13.2×
Miriam Harel · 1×
Citations per year

Countries citing papers authored by Ya-Lan Sun

Since Specialization
Citations

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

Fields of papers citing papers by Ya-Lan Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ya-Lan Sun. 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 Ya-Lan Sun. The network helps show where Ya-Lan Sun may publish in the future.

Co-authors

The 25 scholars most cited alongside Ya-Lan Sun, 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 Ya-Lan Sun Line = papers co-authored together Ya-Lan Sun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009239
2 2012144
3 2011110
4 200654
5 201837
6 202235
7 200830
8 201329
9 202127
10 202225
11 202224
12 202019
13 202018
14 202311
15 202011
16 20219
17 20228
18 20248
19 20227
20 20206

About Ya-Lan Sun

Ya-Lan Sun is a scholar working on Cellular and Molecular Neuroscience, Insect Science, Molecular Biology, Genetics and Ecology, Evolution, Behavior and Systematics, having authored 29 papers that have together received 861 indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (13 papers), Insect and Arachnid Ecology and Behavior (7 papers), Insect-Plant Interactions and Control (6 papers), Insect Resistance and Genetics (5 papers), Plant and animal studies (4 papers), Insect Utilization and Effects (3 papers), Insect Pheromone Research and Control (3 papers) and Insect and Pesticide Research (2 papers). The work is most often cited by research in Obstetrics and Gynecology (171 citations), Insect Science (256 citations), Cellular and Molecular Neuroscience (310 citations), Geophysics (110 citations) and Genetics (148 citations). Ya-Lan Sun has collaborated with scholars based in China, Italy and Taiwan. Frequent co-authors include Chen‐Zhu Wang, Ling‐Qiao Huang, Chen‐Kan Tseng, Will Wei-Cheng Chiu, Paolo Pelosi, Jun-Feng Dong, Nan Li, M. Santosh, Junming Yao and Yanjing Chen. Their work appears in journals such as Insects, Frontiers in Physiology, Frontiers in Endocrinology, PLoS ONE and Journal of Insect Physiology.

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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