Feng Yi

1.7k citations
32 papers · 1.3k · 1 hit paper · h-index 16

Impact in

Papers in

Feng Yi

29 papers receiving 1.2k citations

Feng Yi's Hit Papers

Structure, function, and allosteric modulation of NMDA receptors 2018 · 413 citations
4130+2+5Years since publication100200300400

Peers

Feng Yi
Comparison fields: 5 of 86
  • Cellular and Molecular Neuroscience 837
  • Biological Psychiatry 73
  • Developmental Neuroscience 55
  • Sensory Systems 53
  • Cognitive Neuroscience 188
Replace Florence Gaven with:
Florence Gaven France
Riley E. Perszyk United States
Chian‐Ming Low Singapore
Hideko Yamamoto Japan
Shujia Zhu China
Arturas Volianskis United Kingdom
Yasushi Yabuki Japan
Kevin Erreger United States
I.A. Paterson Canada
David S. Reynolds United Kingdom
Feng Yi relative to Florence Gaven France Florence Gaven's profile →
Citations per field
00.5×
Florence Gaven · 1×
Citations per year

Countries citing papers authored by Feng Yi

Since Specialization
Citations

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

Fields of papers citing papers by Feng Yi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Structure, function, and allosteric modulation of NMDA receptors
Hit paper breakdown →
2018413
2 2017141
3 2012103
4 2014103
5 201683
6 201855
7 201954
8 201539
9 202028
10 201828
11 201426
12 201726
13 201524
14 201720
15 201719
16 202015
17 201714
18 201914
19 202311
20 20207

About Feng Yi

Feng Yi is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Cognitive Neuroscience, Organic Chemistry and Biochemistry, having authored 32 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (29 papers), Ion channel regulation and function (11 papers), Receptor Mechanisms and Signaling (10 papers), Chemical Synthesis and Analysis (8 papers), Memory and Neural Mechanisms (4 papers), Nicotinic Acetylcholine Receptors Study (3 papers), Amino Acid Enzymes and Metabolism (3 papers) and Neural dynamics and brain function (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (837 citations), Biological Psychiatry (73 citations), Developmental Neuroscience (55 citations), Sensory Systems (53 citations) and Cognitive Neuroscience (188 citations). Feng Yi has collaborated with scholars based in United States, China and Denmark. Frequent co-authors include Kasper B. Hansen, Stephen F. Traynelis, Riley E. Perszyk, Lonnie P. Wollmuth, Hiro Furukawa, Alasdair J. Gibb, Frank S. Menniti, J. Josh Lawrence, Subhrajit Bhattacharya and Karl Deisseroth. Their work appears in journals such as Molecular Pharmacology, ACS Chemical Neuroscience, Neuropharmacology, Journal of Medicinal Chemistry and The Journal of General 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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