Kunlin Jin

24.8k total citations · 4 hit papers
226 papers, 19.1k citations indexed

About

Kunlin Jin is a scholar working on Molecular Biology, Developmental Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kunlin Jin has authored 226 papers receiving a total of 19.1k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Molecular Biology, 67 papers in Developmental Neuroscience and 56 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kunlin Jin's work include Neurogenesis and neuroplasticity mechanisms (62 papers), Neuroinflammation and Neurodegeneration Mechanisms (46 papers) and Axon Guidance and Neuronal Signaling (21 papers). Kunlin Jin is often cited by papers focused on Neurogenesis and neuroplasticity mechanisms (62 papers), Neuroinflammation and Neurodegeneration Mechanisms (46 papers) and Axon Guidance and Neuronal Signaling (21 papers). Kunlin Jin collaborates with scholars based in United States, China and India. Kunlin Jin's co-authors include David A. Greenberg, Xiao Mao, Lin Xie, Yunjuan Sun, Anna Logvinova, Yonghua Zhu, Jocelyn Childs, Alyson Peel, Roger P. Simon and Brian Wang and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.

In The Last Decade

Kunlin Jin

223 papers receiving 18.8k citations

Hit Papers

Vascular endothelial grow... 2002 2026 2010 2018 2002 2003 2003 2003 400 800 1.2k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kunlin Jin 7.5k 5.6k 5.2k 4.6k 2.7k 226 19.1k
Seung Up Kim 9.8k 1.3× 5.0k 0.9× 5.6k 1.1× 4.3k 0.9× 3.5k 1.3× 839 32.8k
V. Wee Yong 10.0k 1.3× 3.6k 0.7× 4.4k 0.8× 7.8k 1.7× 2.4k 0.9× 437 30.1k
Jack P. Antel 11.1k 1.5× 4.9k 0.9× 3.9k 0.7× 10.9k 2.4× 2.9k 1.1× 525 38.0k
Zaal Kokaia 7.1k 0.9× 10.9k 2.0× 10.0k 1.9× 6.0k 1.3× 1.6k 0.6× 165 20.8k
Bruce D. Trapp 11.3k 1.5× 8.7k 1.6× 8.4k 1.6× 8.3k 1.8× 3.2k 1.2× 277 34.3k
Frank R. Sharp 12.3k 1.6× 2.8k 0.5× 7.3k 1.4× 5.4k 1.2× 3.9k 1.5× 376 27.7k
Klaus‐Armin Nave 15.0k 2.0× 9.9k 1.8× 11.4k 2.2× 6.3k 1.4× 3.4k 1.3× 296 32.1k
Michael Sendtner 10.0k 1.3× 4.8k 0.9× 8.2k 1.6× 1.7k 0.4× 1.3k 0.5× 225 20.1k
Mathias Bähr 9.2k 1.2× 2.6k 0.5× 5.9k 1.1× 2.8k 0.6× 1.7k 0.6× 356 17.3k
Robin J.M. Franklin 9.7k 1.3× 14.7k 2.6× 8.0k 1.5× 10.0k 2.2× 1.9k 0.7× 293 29.1k

Countries citing papers authored by Kunlin Jin

Since Specialization
Citations

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

Fields of papers citing papers by Kunlin Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kunlin Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Kunlin Jin. A scholar is included among the top collaborators of Kunlin Jin 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 Kunlin Jin. Kunlin Jin 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.
Zhang, Ying, et al.. (2024). Exosomes from polarized Microglia: Proteomic insights into potential mechanisms affecting intracerebral hemorrhage. Gene. 935. 149080–149080. 1 indexed citations
2.
Wang, Jixian, Yongfang Li, Guo-Yuan Yang, & Kunlin Jin. (2024). Age-Related Dysfunction in Balance: A Comprehensive Review of Causes, Consequences, and Interventions. Aging and Disease. 16(2). 714–714. 21 indexed citations
3.
Wang, Xi, Li Ma, Sheng Jiang, et al.. (2024). Expert Consensus on Prevention and Treatment of Aging-Related Gonadal Dysfunction. Aging and Disease. 16(2). 971–979. 1 indexed citations
4.
Wang, Brian, et al.. (2024). Cerebellum and Aging: Update and Challenges. Aging and Disease. 15(6). 2345–2360. 7 indexed citations
5.
Ren, Chang­hong, Ning Li, Linpei Jia, et al.. (2024). Hypoxic Conditioning: A Potential Perioperative Strategy to Reduce Abdominal Aortic Occlusion-Related Injury in Mouse Proximal and Distal Organs. Aging and Disease. 15(6). 2863–2879. 2 indexed citations
7.
Wang, Hao, et al.. (2023). NeuroD4 converts glioblastoma cells into neuron-like cells through the SLC7A11-GSH-GPX4 antioxidant axis. Cell Death Discovery. 9(1). 297–297. 9 indexed citations
8.
Luo, Yuqi, Xingfang Guo, Wanlin Yang, et al.. (2023). Healthy Human Fecal Microbiota Transplantation into Mice Attenuates MPTP-Induced Neurotoxicity via AMPK/SOD2 Pathway. Aging and Disease. 14(6). 2193–2193. 42 indexed citations
9.
Jin, Kunlin. (2023). Brain‐X: A new interdisciplinary journal for advancing neuroscience research. SHILAP Revista de lepidopterología. 1(1).
10.
Lin, Xiao, Hao Wang, Zhongxiao Lin, et al.. (2022). Transplantation of Roxadustat‐preconditioned bone marrow stromal cells improves neurological function recovery through enhancing grafted cell survival in ischemic stroke rats. CNS Neuroscience & Therapeutics. 28(10). 1519–1531. 22 indexed citations
11.
Zhang, Hongxia, et al.. (2021). Circulating Pro-Inflammatory Exosomes Worsen Stroke Outcomes in Aging. Circulation Research. 129(7). e121–e140. 43 indexed citations
12.
Chakrabarti, Sankha Shubhra, Sankha Shubhra Chakrabarti, Upinder Kaur, et al.. (2020). Of Cross-Immunity, Herd Immunity and Country-Specific Plans: Experiences from COVID-19 in India. SSRN Electronic Journal. 1 indexed citations
13.
Pan, Jiaji, Muyassar Mamtilahun, Yuan Zhu, et al.. (2019). Microglia exacerbate white matter injury via complement C3/C3aR pathway after hypoperfusion. Theranostics. 10(1). 74–90. 140 indexed citations
14.
Pan, Mengxiong, Hongxia Zhang, Siyang Lin, et al.. (2017). Aging Systemic Milieu Impairs Outcome after Ischemic Stroke in Rats. Aging and Disease. 8(5). 519–519. 16 indexed citations
15.
Liang, Zhanfeng, Yang Zhao, Yang Zhao, et al.. (2017). Impact of aging immune system on neurodegeneration and potential immunotherapies. Progress in Neurobiology. 157. 2–28. 43 indexed citations
16.
Yao, Yu, Hongxing Ye, Zengxin Qi, et al.. (2016). B7-H4(B7x)–Mediated Cross-talk between Glioma-Initiating Cells and Macrophages via the IL6/JAK/STAT3 Pathway Lead to Poor Prognosis in Glioma Patients. Clinical Cancer Research. 22(11). 2778–2790. 148 indexed citations
17.
Sun, Fen, XiaoOu Mao, Lin Xie, et al.. (2013). Notch1 signaling modulates neuronal progenitor activity in the subventricular zone in response to aging and focal ischemia. Aging Cell. 12(6). 978–987. 52 indexed citations
18.
Zhuge, Qichuan, Ming Zhong, Weiming Zheng, et al.. (2009). Notch-1 signalling is activated in brain arteriovenous malformations in humans. Brain. 132(12). 3231–3241. 74 indexed citations
19.
Jin, Kunlin, Xiaomei Wang, Lin Xie, et al.. (2006). Evidence for stroke-induced neurogenesis in the human brain. Proceedings of the National Academy of Sciences. 103(35). 13198–13202. 475 indexed citations
20.
Jin, Kunlin, Manabu Minami, Lin Xie, et al.. (2004). Ischemia‐induced neurogenesis is preserved but reduced in the aged rodent brain. Aging Cell. 3(6). 373–377. 99 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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