Long Li

3.3k total citations · 1 hit paper
49 papers, 1.8k citations indexed

About

Long Li is a scholar working on Molecular Biology, Genetics and Behavioral Neuroscience. According to data from OpenAlex, Long Li has authored 49 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 9 papers in Genetics and 8 papers in Behavioral Neuroscience. Recurrent topics in Long Li's work include Stress Responses and Cortisol (8 papers), Neuroendocrine regulation and behavior (6 papers) and Tryptophan and brain disorders (6 papers). Long Li is often cited by papers focused on Stress Responses and Cortisol (8 papers), Neuroendocrine regulation and behavior (6 papers) and Tryptophan and brain disorders (6 papers). Long Li collaborates with scholars based in China, United States and Taiwan. Long Li's co-authors include Eunyong Park, Tom A. Rapoport, Xiaoqun Wang, Qian Wu, Le Sun, Fuchou Tang, Xiaohui Xu, Haofeng Zhang, Na Pan and Ji Dong and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Long Li

47 papers receiving 1.7k citations

Hit Papers

A single-cell RNA-seq survey of the developmental landsca... 2018 2026 2020 2023 2018 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Long Li China 18 871 263 169 165 162 49 1.8k
Zhe Jin Sweden 28 926 1.1× 430 1.6× 231 1.4× 364 2.2× 678 4.2× 104 2.8k
Narendrakumar Ramanan United States 17 955 1.1× 186 0.7× 136 0.8× 91 0.6× 602 3.7× 30 2.0k
Lennart Opitz Switzerland 28 2.1k 2.4× 606 2.3× 148 0.9× 215 1.3× 390 2.4× 79 3.4k
Masaharu Hayashi Japan 29 983 1.1× 412 1.6× 100 0.6× 254 1.5× 399 2.5× 135 2.6k
Hélène Tricoire-Leignel France 18 624 0.7× 185 0.7× 100 0.6× 500 3.0× 290 1.8× 30 2.2k
Tsuyoshi Koide Japan 25 1.1k 1.3× 731 2.8× 105 0.6× 109 0.7× 439 2.7× 94 2.4k
Elena Maksimova United States 18 1.4k 1.7× 235 0.9× 70 0.4× 109 0.7× 285 1.8× 32 2.1k
Carla Mucignat‐Caretta Italy 26 647 0.7× 259 1.0× 256 1.5× 79 0.5× 635 3.9× 129 2.6k
Igor Ponomarev United States 24 1.0k 1.2× 292 1.1× 116 0.7× 472 2.9× 745 4.6× 93 2.4k
Min Deng China 21 1.2k 1.4× 236 0.9× 266 1.6× 41 0.2× 242 1.5× 36 1.7k

Countries citing papers authored by Long Li

Since Specialization
Citations

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

Fields of papers citing papers by Long Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Long Li

This figure shows the co-authorship network connecting the top 25 collaborators of Long Li. A scholar is included among the top collaborators of Long Li based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Long Li. Long Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Long, Hsiao‐Yun Lin, Lyonna F. Parise, et al.. (2025). Targeting neuronal activity and neuroinflammation for the treatment of Alzheimer’s disease in a mouse model. Neurobiology of Aging. 157. 111–118.
3.
Montgomery, Sarah, Long Li, Scott J. Russo, et al.. (2023). Mesolimbic Neural Response Dynamics Predict Future Individual Alcohol Drinking in Mice. Biological Psychiatry. 95(10). 951–962. 4 indexed citations
4.
Cuttoli, Romain Durand-de, Freddyson J. Martínez-Rivera, Long Li, et al.. (2023). A Double Hit of Social and Economic Stress in Mice Precipitates Changes in Decision-Making Strategies. Biological Psychiatry. 96(1). 67–78. 4 indexed citations
5.
Li, Long, Yajun Cao, Minguang Yang, et al.. (2023). Electroacupuncture promotes neurogenesis in the dentate gyrus and improves pattern separation in an early Alzheimer's disease mouse model. Biological Research. 56(1). 65–65. 7 indexed citations
6.
Shimo, Yusuke, Flurin Cathomas, Hsiao‐Yun Lin, et al.. (2023). Social stress induces autoimmune responses against the brain. Proceedings of the National Academy of Sciences. 120(49). e2305778120–e2305778120. 10 indexed citations
7.
Takahashi, Aki, Romain Durand-de Cuttoli, Meghan E. Flanigan, et al.. (2022). Lateral habenula glutamatergic neurons projecting to the dorsal raphe nucleus promote aggressive arousal in mice. Nature Communications. 13(1). 4039–4039. 21 indexed citations
8.
Zhang, Wenjing, Lingting Zeng, Huan Yu, et al.. (2022). Injectable spontaneous hydrogen-releasing hydrogel for long-lasting alleviation of osteoarthritis. Acta Biomaterialia. 158. 163–177. 44 indexed citations
9.
Li, Long, Jianhong Li, Yaling Dai, et al.. (2022). Electro-Acupuncture Improve the Early Pattern Separation in Alzheimer’s Disease Mice via Basal Forebrain-Hippocampus Cholinergic Neural Circuit. Frontiers in Aging Neuroscience. 13. 770948–770948. 15 indexed citations
10.
Morel, Carole, Sarah Montgomery, Long Li, et al.. (2022). Midbrain projection to the basolateral amygdala encodes anxiety-like but not depression-like behaviors. Nature Communications. 13(1). 1532–1532. 103 indexed citations
11.
Sun, Le, Ruiguo Chen, Long Li, et al.. (2020). Visualization and correction of social abnormalities-associated neural ensembles in adult MECP2 duplication mice. Science Bulletin. 65(14). 1192–1202. 12 indexed citations
12.
Zhong, Suijuan, Shu Zhang, Xiaoying Fan, et al.. (2018). A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex. Nature. 555(7697). 524–528. 408 indexed citations breakdown →
13.
Liu, Qingmei, Sha-sha Xu, Long Li, et al.. (2017). In vitro and in vivo immunomodulatory activity of sulfated polysaccharide from Porphyra haitanensis. Carbohydrate Polymers. 165. 189–196. 118 indexed citations
14.
Li, Ruixue, Dandan Chen, Yizhen Wan, et al.. (2017). High throughput deep degradome sequencing reveals microRNAs and their targets in response to drought stress in mulberry (Morus alba). PLoS ONE. 12(2). e0172883–e0172883. 19 indexed citations
15.
Liu, Jing, Wensu Liu, Lu Yang, et al.. (2017). The Primate-Specific Gene TMEM14B Marks Outer Radial Glia Cells and Promotes Cortical Expansion and Folding. Cell stem cell. 21(5). 635–649.e8. 91 indexed citations
16.
Li, Zhibin, Changqin Liu, Xiulin Shi, et al.. (2017). Common genetic variants in the FETUB locus, genetically predicted fetuin-B levels, and risk of insulin resistance in obese Chinese adults. Medicine. 96(50). e9234–e9234. 7 indexed citations
17.
Li, Long, Eunyong Park, Jingjing Ling, et al.. (2016). Crystal structure of a substrate-engaged SecY protein-translocation channel. Nature. 531(7594). 395–399. 137 indexed citations
19.
Xu, Wenliang, Yanfeng Wu, Lixia Qin, et al.. (2013). Cotton PRP5 gene encoding a proline-rich protein is involved in fiber development. Plant Molecular Biology. 82(4-5). 353–365. 37 indexed citations
20.
Li, Long & David J. Pintel. (2012). Splicing of goose parvovirus pre-mRNA influences cytoplasmic translation of the processed mRNA. Virology. 426(1). 60–65. 5 indexed citations

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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