Guobin Song

3.0k total citations · 1 hit paper
26 papers, 710 citations indexed

About

Guobin Song is a scholar working on Molecular Biology, Immunology and Neurology. According to data from OpenAlex, Guobin Song has authored 26 papers receiving a total of 710 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 8 papers in Immunology and 5 papers in Neurology. Recurrent topics in Guobin Song's work include Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Antibiotic Resistance in Bacteria (4 papers) and interferon and immune responses (3 papers). Guobin Song is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Antibiotic Resistance in Bacteria (4 papers) and interferon and immune responses (3 papers). Guobin Song collaborates with scholars based in China, United States and Germany. Guobin Song's co-authors include Jinhao Zhang, Xixi Xie, Hao Chi, Jinyan Yang, Gaoge Peng, Lisa J. Pagliari, Prodromos Sidiropoulos, Richard M. Pope, Josef Anrather and Hongtao Liu and has published in prestigious journals such as The Journal of Immunology, Frontiers in Immunology and Journal of the Neurological Sciences.

In The Last Decade

Guobin Song

22 papers receiving 700 citations

Hit Papers

T-cell exhaustion signatures characterize the immune land... 2023 2026 2024 2025 2023 25 50 75

Peers

Guobin Song
Eric D. Strauch United States
Éric Chevalier United States
Nuruddeen D. Lewis United States
Guobin Song
Citations per year, relative to Guobin Song Guobin Song (= 1×) peers Yannan Qin

Countries citing papers authored by Guobin Song

Since Specialization
Citations

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

Fields of papers citing papers by Guobin Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guobin Song

This figure shows the co-authorship network connecting the top 25 collaborators of Guobin Song. A scholar is included among the top collaborators of Guobin Song 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 Guobin Song. Guobin Song 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, Jinhao, Lu Zeng, Guobin Song, et al.. (2025). A novel tertiary lymphoid structure-associated signature accurately predicts patient prognosis and facilitates the selection of personalized treatment strategies for HNSCC. Frontiers in Immunology. 16. 1551844–1551844. 1 indexed citations
2.
Zhang, Tianhao, et al.. (2025). The potential of exogenous specialized pro-resolving mediators in protecting against sepsis-associated lung injury: a review. Frontiers in Pharmacology. 16. 1622754–1622754.
3.
Ding, Yuanyuan, Dong‐Hua Yang, Guobin Song, et al.. (2025). Identification of potential hub genes and drugs in septic kidney injury: a bioinformatic analysis with preliminary experimental validation. Frontiers in Medicine. 12. 1502189–1502189. 1 indexed citations
4.
Song, Guobin, Haoyang Wu, Haiqing Chen, et al.. (2024). hdWGCNA and Cellular Communication Identify Active NK CellSubtypes in Alzheimer's Disease and Screen for Diagnostic Markersthrough Machine Learning. Current Alzheimer Research. 21(2). 120–140. 1 indexed citations
5.
Chi, Hao, Gaoge Peng, Guobin Song, et al.. (2024). Deciphering a Prognostic Signature Based on Soluble Mediators Defines the Immune Landscape and Predicts Prognosis in HNSCC. Frontiers in Bioscience-Landmark. 29(3). 5 indexed citations
6.
Chen, Xinfei, Minya Lu, Yao Wang, et al.. (2024). Emergence and clonal expansion of Aeromonas hydrophila ST1172 that simultaneously produces MOX-13 and OXA-724. Antimicrobial Resistance and Infection Control. 13(1). 28–28. 1 indexed citations
7.
Chi, Hao, Songyun Zhao, Jinyan Yang, et al.. (2023). T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing. Frontiers in Immunology. 14. 1137025–1137025. 97 indexed citations breakdown →
8.
Zhang, Jinhao, Gaoge Peng, Hao Chi, et al.. (2023). CD8 + T-cell marker genes reveal different immune subtypes of oral lichen planus by integrating single-cell RNA-seq and bulk RNA-sequencing. BMC Oral Health. 23(1). 47 indexed citations
9.
Chi, Hao, Jinyan Yang, Gaoge Peng, et al.. (2023). Circadian rhythm-related genes index: A predictor for HNSCC prognosis, immunotherapy efficacy, and chemosensitivity. Frontiers in Immunology. 14. 1091218–1091218. 61 indexed citations
10.
Song, Guobin, Gaoge Peng, Jinhao Zhang, et al.. (2023). Uncovering the potential role of oxidative stress in the development of periodontitis and establishing a stable diagnostic model via combining single-cell and machine learning analysis. Frontiers in Immunology. 14. 1181467–1181467. 29 indexed citations
11.
Chi, Hao, Gaoge Peng, Jinyan Yang, et al.. (2022). Machine learning to construct sphingolipid metabolism genes signature to characterize the immune landscape and prognosis of patients with uveal melanoma. Frontiers in Endocrinology. 13. 1056310–1056310. 41 indexed citations
12.
Peng, Gaoge, Hao Chi, Jinhao Zhang, et al.. (2022). Identification and validation of neurotrophic factor-related genes signature in HNSCC to predict survival and immune landscapes. Frontiers in Genetics. 13. 1010044–1010044. 36 indexed citations
13.
Song, Guobin, et al.. (2021). A Rapid Antimicrobial Susceptibility Test for Klebsiella pneumoniae Using a Broth Micro-Dilution Combined with MALDI TOF MS. Infection and Drug Resistance. Volume 14. 1823–1831. 9 indexed citations
14.
Liu, Xiaoqin, Xiaojuan Zhang, Peijun Zhang, et al.. (2021). Mdivi-1 Modulates Macrophage/Microglial Polarization in Mice with EAE via the Inhibition of the TLR2/4-GSK3β-NF-κB Inflammatory Signaling Axis. Molecular Neurobiology. 59(1). 1–16. 31 indexed citations
15.
Song, Guobin, et al.. (2020). Double triggers, nasal induction of a Parkinson’s disease mouse model. Neuroscience Letters. 724. 134869–134869. 2 indexed citations
16.
Song, Guobin, et al.. (2020). <p>Association of CRISPR/Cas System with the Drug Resistance in <em>Klebsiella pneumoniae</em></p>. Infection and Drug Resistance. Volume 13. 1929–1935. 30 indexed citations
18.
Lǐ, Yànhuá, Fang Xu, Rodolfo Thomé, et al.. (2019). Mdivi-1, a mitochondrial fission inhibitor, modulates T helper cells and suppresses the development of experimental autoimmune encephalomyelitis. Journal of Neuroinflammation. 16(1). 149–149. 43 indexed citations
19.
Yu, Jingwen, Yanhua Li, Guobin Song, et al.. (2016). Synergistic and Superimposed Effect of Bone Marrow-Derived Mesenchymal Stem Cells Combined with Fasudil in Experimental Autoimmune Encephalomyelitis. Journal of Molecular Neuroscience. 60(4). 486–497. 16 indexed citations
20.
Liu, Hongtao, Prodromos Sidiropoulos, Guobin Song, et al.. (2000). TNF-α Gene Expression in Macrophages: Regulation by NF-κB Is Independent of c-Jun or C/EBPβ. The Journal of Immunology. 164(8). 4277–4285. 191 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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