Xiaobo Wang

8.2k total citations · 4 hit papers
184 papers, 5.6k citations indexed

About

Xiaobo Wang is a scholar working on Molecular Biology, Genetics and Epidemiology. According to data from OpenAlex, Xiaobo Wang has authored 184 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Molecular Biology, 30 papers in Genetics and 29 papers in Epidemiology. Recurrent topics in Xiaobo Wang's work include Liver Disease Diagnosis and Treatment (21 papers), Genetic Mapping and Diversity in Plants and Animals (11 papers) and Phagocytosis and Immune Regulation (11 papers). Xiaobo Wang is often cited by papers focused on Liver Disease Diagnosis and Treatment (21 papers), Genetic Mapping and Diversity in Plants and Animals (11 papers) and Phagocytosis and Immune Regulation (11 papers). Xiaobo Wang collaborates with scholars based in China, United States and Italy. Xiaobo Wang's co-authors include Ira Tabas, Ze Zheng, Jiliang Zhou, Arif Yurdagul, Robert F. Schwabe, Guoqing Hu, Bishuang Cai, Xiao Xu, Brennan D. Gerlach and Luca Valenti and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and SHILAP Revista de lepidopterología.

In The Last Decade

Xiaobo Wang

174 papers receiving 5.6k citations

Hit Papers

Macrophage Metabolism of Apoptotic Cell-Derived Argi... 2016 2026 2019 2022 2020 2016 2021 2024 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaobo Wang China 39 2.4k 1.1k 1.1k 753 578 184 5.6k
Xiao‐Ming Yin United States 38 3.7k 1.5× 1.6k 1.4× 695 0.7× 453 0.6× 293 0.5× 122 6.3k
Shanshan Li China 42 2.5k 1.0× 822 0.7× 578 0.5× 438 0.6× 751 1.3× 247 5.4k
Cynthia A. Bradham United States 28 3.0k 1.2× 893 0.8× 704 0.7× 381 0.5× 180 0.3× 52 5.5k
Thorsten Berger Canada 32 2.6k 1.1× 763 0.7× 1.2k 1.1× 333 0.4× 207 0.4× 48 6.0k
Shu Zhang China 47 4.6k 1.9× 1.2k 1.1× 1.3k 1.2× 482 0.6× 399 0.7× 351 9.6k
Cheng Zhang China 43 3.1k 1.3× 535 0.5× 907 0.9× 461 0.6× 640 1.1× 297 6.3k
Fuquan Yang China 43 4.7k 1.9× 584 0.5× 847 0.8× 574 0.8× 569 1.0× 173 7.9k
Seok‐Geun Lee South Korea 51 3.7k 1.5× 825 0.7× 598 0.6× 262 0.3× 389 0.7× 200 7.8k
David Camp United States 61 7.5k 3.1× 1.2k 1.1× 754 0.7× 733 1.0× 327 0.6× 152 11.7k
Alberto Álvarez Spain 52 4.2k 1.7× 993 0.9× 966 0.9× 545 0.7× 273 0.5× 155 8.2k

Countries citing papers authored by Xiaobo Wang

Since Specialization
Citations

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

Fields of papers citing papers by Xiaobo Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaobo Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaobo Wang. A scholar is included among the top collaborators of Xiaobo Wang 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 Xiaobo Wang. Xiaobo Wang 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.
Wang, Xiaobo, Hongxue Shi, Yang Xiao, et al.. (2025). A non-apoptotic caspase-8–meteorin pathway in hepatocytes promotes MASH fibrosis. Nature Metabolism. 7(10). 2067–2082.
2.
Zhang, Hui, et al.. (2024). Combination of serum alpha-fetoprotein, PIVKA-Ⅱ and glypican-3 in diagnosis of hepatocellular carcinoma: a meta-analysis. Journal of Zhejiang University (Medical Sciences). 53(1). 131–139.
3.
Li, Man, Yuchen Ge, Jing Xia, et al.. (2024). Atorvastatin calcium alleviates UVB-induced HaCat cell senescence and skin photoaging. Scientific Reports. 14(1). 30010–30010. 5 indexed citations
4.
Ampomah, Patrick B., Lancia Darville, Xiaobo Wang, et al.. (2024). Efferocytosis drives a tryptophan metabolism pathway in macrophages to promote tissue resolution. Nature Metabolism. 6(9). 1736–1755. 31 indexed citations
5.
Wang, Xiaobo, Liang Zhang, & Bingning Dong. (2024). Molecular mechanisms in MASLD/MASH-related HCC. Hepatology. 82(5). 1303–1324. 62 indexed citations breakdown →
7.
Wang, Xiaobo, et al.. (2023). Protection of Substation Grounding Grid by Gadolinium Magnesium Sacrificial Anode. Journal of Physics Conference Series. 2546(1). 12004–12004. 1 indexed citations
8.
Shi, Hongxue, et al.. (2023). Efferocytosis in liver disease. JHEP Reports. 6(1). 100960–100960. 18 indexed citations
9.
Wang, Xiaobo. (2022). Challenges and opportunities in nonalcoholic steatohepatitis. SHILAP Revista de lepidopterología. 2(4). 328–330. 3 indexed citations
10.
Ampomah, Patrick B., Bishuang Cai, Brennan D. Gerlach, et al.. (2022). Macrophages use apoptotic cell-derived methionine and DNMT3A during efferocytosis to promote tissue resolution. Nature Metabolism. 4(4). 444–457. 98 indexed citations
11.
Shi, Hongxue, Xiaobo Wang, Fang Li, et al.. (2022). CD47-SIRPα axis blockade in NASH promotes necroptotic hepatocyte clearance by liver macrophages and decreases hepatic fibrosis. Science Translational Medicine. 14(672). eabp8309–eabp8309. 55 indexed citations
12.
Yu, Junjie, Changyu Zhu, Xiaobo Wang, et al.. (2021). Hepatocyte TLR4 triggers inter-hepatocyte Jagged1/Notch signaling to determine NASH-induced fibrosis. Science Translational Medicine. 13(599). 94 indexed citations
13.
Li, Wen, Xiaobo Wang, & Yan Xu. (2021). Recognition of CRISPR Off-Target Cleavage Sites with SeqGAN. Current Bioinformatics. 17(1). 101–107. 6 indexed citations
14.
Zheng, Ze, Keiko Nakamura, Xiaobo Wang, et al.. (2020). Interacting hepatic PAI-1/tPA gene regulatory pathways influence impaired fibrinolysis severity in obesity. Journal of Clinical Investigation. 130(8). 4348–4359. 28 indexed citations
15.
Tao, Wei, Arif Yurdagul, Na Kong, et al.. (2020). siRNA nanoparticles targeting CaMKIIγ in lesional macrophages improve atherosclerotic plaque stability in mice. Science Translational Medicine. 12(553). 191 indexed citations
16.
Fu, Hongli, Yingxi Yang, Xiaobo Wang, Hui Wang, & Yan Xu. (2019). DeepUbi: a deep learning framework for prediction of ubiquitination sites in proteins. BMC Bioinformatics. 20(1). 86–86. 57 indexed citations
17.
Hou, Biyu, Guifen Qiang, Xiuying Yang, et al.. (2018). Puerarin Mitigates Diabetic Hepatic Steatosis and Fibrosis by Inhibiting TGF‐β Signaling Pathway Activation in Type 2 Diabetic Rats. Oxidative Medicine and Cellular Longevity. 2018(1). 4545321–4545321. 52 indexed citations
18.
Wang, Xiaobo, et al.. (2017). Acute toxicity of low molecular seleno-aminopolysaccharide to mice.. Zhongguo shouyi xuebao. 37(9). 1790–1796. 2 indexed citations
19.
Pan, Longfei, et al.. (2016). The usage of HC visual laryngoscope for emergency tracheal intubation by unskilled junior emergency resident doctors. Zhonghua jizhen yixue zazhi. 25(7). 910–914. 2 indexed citations
20.
Xu, Wanhong, Brian Xi, Jieying Wu, et al.. (2009). Natural product derivative Bis(4-fluorobenzyl)trisulfide inhibits tumor growth by modification of β-tubulin at Cys 12 and suppression of microtubule dynamics. Molecular Cancer Therapeutics. 8(12). 3318–3330. 22 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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