Ying‐Wan Lam

1.4k citations
21 papers · 988 · h-index 18

Impact in

Papers in

Ying‐Wan Lam

21 papers receiving 956 citations

Peers

Ying‐Wan Lam
Comparison fields: 5 of 77
  • Sensory Systems 175
  • Cognitive Neuroscience 685
  • Cellular and Molecular Neuroscience 636
  • Behavioral Neuroscience 47
  • Nutrition and Dietetics 68
Replace Carien S. Lansink with:
Carien S. Lansink Netherlands
Bernard Hars France
Nicole K. Horst United States
Jeffrey C. Erlich United States
Houri Hintiryan United States
Vijay Mohan K Namboodiri United States
Joshua I. Sanders United States
Marina A. Belova United States
Henry Lütcke Switzerland
Tania Rinaldi Barkat Switzerland
Ying‐Wan Lam relative to Carien S. Lansink Netherlands Carien S. Lansink's profile →
Citations per field
00.5×1.5×1.9×
Carien S. Lansink · 1×
Citations per year

Countries citing papers authored by Ying‐Wan Lam

Since Specialization
Citations

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

Fields of papers citing papers by Ying‐Wan Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ying‐Wan Lam. 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 Ying‐Wan Lam. The network helps show where Ying‐Wan Lam may publish in the future.

Co-authors

The 23 scholars most cited alongside Ying‐Wan Lam, 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 Ying‐Wan Lam Line = papers co-authored together Ying‐Wan Lam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996137
2 2000132
3 199697
4 200987
5 201179
6 200657
7 200749
8 199448
9 200548
10 199847
11 201437
12 200325
13 201323
14 201222
15
Concepts in Imaging and Microscopy Imaging Membrane Potential With Voltage-Sensitive Dyes
200022
16 200520
17 201519
18 199617
19 199911
20 20136

About Ying‐Wan Lam

Ying‐Wan Lam is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience, Molecular Biology, Sensory Systems and Physiology, having authored 21 papers that have together received 988 indexed citations. Recurring topics across this work include Photoreceptor and optogenetics research (11 papers), Neuroscience and Neuropharmacology Research (10 papers), Neural dynamics and brain function (9 papers), Neuroscience and Neural Engineering (4 papers), Neurobiology and Insect Physiology Research (3 papers), Olfactory and Sensory Function Studies (3 papers), Retinal Development and Disorders (2 papers) and Advanced Chemical Sensor Technologies (2 papers). The work is most often cited by research in Sensory Systems (175 citations), Cognitive Neuroscience (685 citations), Cellular and Molecular Neuroscience (636 citations), Behavioral Neuroscience (47 citations) and Nutrition and Dietetics (68 citations). Ying‐Wan Lam has collaborated with scholars based in United States. Frequent co-authors include S. Murray Sherman, Néstor A. Schmajuk, J.A. Gray, Lawrence B. Cohen, Michał Żochowski, Matt Wachowiak, Christopher S. Nelson, Charles C. Lee, Chun X. Falk and Rona J. Delay. Their work appears in journals such as Journal of Neurophysiology, Neuroscience, Journal of Neuroscience, European Journal of Neuroscience and Neuroreport.

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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