Li Lu

4.7k citations
111 papers · 3.1k · 1 hit paper · h-index 30

Impact in

Papers in

Li Lu

98 papers receiving 3.1k citations

Li Lu's Hit Papers

Coordination of entorhinal–hippocampal ensemble activity during associative learning 2014 · 307 citations
3070+4+8Years since publication100200300

Peers

Li Lu
Comparison fields: 5 of 144
  • Cellular and Molecular Neuroscience 820
  • Cognitive Neuroscience 807
  • Developmental Neuroscience 123
  • Sensory Systems 117
  • Toxicology 79
Replace Emilio Casanova with:
Emilio Casanova Austria
Ling Pan China
Faramarz Dehghani Germany
Christopher J. Davis United States
Douglas A. Lappi United States
Harald Höger Austria
Mei Zhao China
Shoichi Masushige Japan
Gareth Pryce United Kingdom
Kyungmin Lee South Korea
Li Lu relative to Emilio Casanova Austria Emilio Casanova's profile →
Citations per field
00.5×1.5×2.3×
Emilio Casanova · 1×
Citations per year

Countries citing papers authored by Li Lu

Since Specialization
Citations

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

Fields of papers citing papers by Li Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Coordination of entorhinal–hippocampal ensemble activity during associative learning
Hit paper breakdown →
2014307
2 2018296
3 2021210
4 2011137
5 2015110
6 2010110
7 2020102
8 200793
9 198983
10 201379
11 200776
12 202167
13 201060
14 201960
15 201956
16 200454
17 200950
18 201950
19 200747
20 200946

About Li Lu

Li Lu is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Epidemiology, Oncology and Cell Biology, having authored 111 papers that have together received 3.1k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (11 papers), Ubiquitin and proteasome pathways (7 papers), Neurogenesis and neuroplasticity mechanisms (6 papers), Memory and Neural Mechanisms (6 papers), Multiple Myeloma Research and Treatments (5 papers), Autophagy in Disease and Therapy (5 papers), Natural Compounds in Disease Treatment (4 papers) and Sleep and Wakefulness Research (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (820 citations), Cognitive Neuroscience (807 citations), Developmental Neuroscience (123 citations), Sensory Systems (117 citations) and Toxicology (79 citations). Li Lu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include May‐Britt Moser, Edvard I Moser, Kei M. Igarashi, Laura L Colgin, Albert Tsao, James Knierim, Cheng Wang, Jørgen Sugar, Menno P. Witter and Chung Owyang. Their work appears in journals such as Scientific Reports, European Journal of Pharmacology, Stem Cells, PLoS ONE and International Journal of Biological Macromolecules.

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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