Weidong Li

388 papers receiving 10.7k citations

Weidong Li's Hit Papers

Rapid local acceleration of relativistic radiation-belt electrons by magnetospheric chorus 2013 · 638 citations
6380+6+12Years since publication200400600

Peers

Weidong Li
Comparison fields: 5 of 193
  • Behavioral Neuroscience 264
  • Cancer Research 1.0k
  • Cellular and Molecular Neuroscience 1.3k
  • Developmental Neuroscience 277
  • Cognitive Neuroscience 1.2k
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Citations per field
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Countries citing papers authored by Weidong Li

Since Specialization
Citations

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

Fields of papers citing papers by Weidong Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 422 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Reversal of learning deficits in a Tsc2+/− mouse model of tuberous sclerosis
Hit paper breakdown →
2008655
2
Rapid local acceleration of relativistic radiation-belt electrons by magnetospheric chorus
Hit paper breakdown →
2013638
3 2001417
4 2005300
5 2019298
6 2015295
7 2017250
8 2010224
9 2003208
10 2007169
11 2007165
12 2019162
13 2007144
14 2008143
15 2006112
16 2017109
17 2014107
18 2017101
19 200499
20 201396

About Weidong Li

Weidong Li is a scholar working on Molecular Biology, Oncology, Cellular and Molecular Neuroscience, Cancer Research and Genetics, having authored 422 papers that have together received 10.8k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (24 papers), RNA modifications and cancer (16 papers), Genetics and Neurodevelopmental Disorders (14 papers), MicroRNA in disease regulation (11 papers), Cultural Heritage Materials Analysis (11 papers), Fungal Biology and Applications (10 papers), Memory and Neural Mechanisms (10 papers) and Building materials and conservation (10 papers). The work is most often cited by research in Behavioral Neuroscience (264 citations), Cancer Research (1.0k citations), Cellular and Molecular Neuroscience (1.3k citations), Developmental Neuroscience (277 citations) and Cognitive Neuroscience (1.2k citations). Weidong Li has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Alcino J. Silva, Dan Ehninger, Volker Neugebauer, Yu Zhou, Enyong Ding, Shakir M. Saud, Matthew R. Young, Vijaya Ramesh, Carrie Shilyansky and David J. Kwiatkowski. Their work appears in journals such as Scientific Reports, Molecular Brain, Ceramics International, Psychiatric Genetics and Aquaculture.

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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