Li Shen
- Neurology top 0.5%
- Psychiatry and Mental health top 0.5%
- Dementia and Cognitive Impairment Research 60
- Cognitive Neuroscience top 1%
- Functional Brain Connectivity Studies 75
- Physiology top 0.5%
- Alzheimer's disease research and treatments 62
- Computational Mathematics top 2%
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- Bioinformatics and Genomic Networks 93
- Gene expression and cancer classification 59
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- Genetic Associations and Epidemiology 67
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- Advanced Neuroimaging Techniques and Applications 54
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- Medical Image Segmentation Techniques 25
- Co-authors
- Andrew J. SaykinShannon L. RisacherMichael W. WeinerSungeun KimJingwen YanKwangsik NhoHeng HuangFillia Makedon
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Li Shen
399 papers receiving 10.5k citations
Hit Papers
Peers
Comparison fields: 5 of 204
- Neurology 1.2k
- Psychiatry and Mental health 2.1k
- Cognitive Neuroscience 1.8k
- Physiology 2.2k
- Computational Mathematics 48
Countries citing papers authored by Li Shen
This map shows the geographic impact of Li Shen'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 Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Shen more than expected).
Fields of papers citing papers by Li Shen
This network shows the impact of papers produced by Li Shen. 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 Shen. The network helps show where Li Shen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Li Shen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 5 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 25 | |
| 10 | 2024 | 4 | |
| 11 | 2023 | 4 | |
| 12 | 2023 | 37 | |
| 13 | 2021 | 19 | |
| 14 | 2019 | 51 | |
| 15 | Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data | 2018 | 44 |
| 16 | Hippocampal transcriptome-guided genetic analysis of correlated episodic memory phenotypes in Alzheimer's disease | 2015 | 1 |
| 17 | 2012 | 55 | |
| 18 | 2011 | 51 | |
| 19 | 2003 | 8 | |
| 20 | 1970 | 2 |
About Li Shen
Li Shen is a scholar working on Computational Mathematics, Cognitive Neuroscience and Psychiatry and Mental health, having authored 437 papers that have together received 10.7k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (93 papers), Functional Brain Connectivity Studies (75 papers), Genetic Associations and Epidemiology (67 papers), Alzheimer's disease research and treatments (62 papers), Dementia and Cognitive Impairment Research (60 papers), Gene expression and cancer classification (59 papers), Advanced Neuroimaging Techniques and Applications (54 papers) and Medical Image Segmentation Techniques (25 papers). The work is most often cited by research in Neurology (1.2k citations), Psychiatry and Mental health (2.1k citations) and Cognitive Neuroscience (1.8k citations). Li Shen has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Andrew J. Saykin, Shannon L. Risacher, Michael W. Weiner, Sungeun Kim, Jingwen Yan, Kwangsik Nho, Heng Huang, Fillia Makedon, Clifford R. Jack and Jason H. Moore. Their work appears in journals such as Alzheimer s & Dementia, Bioinformatics, NeuroImage, Medical Image Analysis and Neurobiology of Aging.
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.