Xin Xing

1.4k total citations · 1 hit paper
56 papers, 973 citations indexed

About

Xin Xing is a scholar working on Physiology, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Xin Xing has authored 56 papers receiving a total of 973 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Physiology, 11 papers in Molecular Biology and 9 papers in Artificial Intelligence. Recurrent topics in Xin Xing's work include Diet and metabolism studies (5 papers), Gut microbiota and health (5 papers) and Alzheimer's disease research and treatments (5 papers). Xin Xing is often cited by papers focused on Diet and metabolism studies (5 papers), Gut microbiota and health (5 papers) and Alzheimer's disease research and treatments (5 papers). Xin Xing collaborates with scholars based in China, United States and Canada. Xin Xing's co-authors include Chao Yang, Shuo Fang, Hongda Bi, Xijing Qian, Chen Xu, Yuntong Zhang, Yunpeng Zhao, Yue Wang, Kaihong Ji and Minjuan Wu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Xin Xing

51 papers receiving 964 citations

Hit Papers

Umbilical Cord-Derived Mesenchymal Stem Cell-Derived Exos... 2016 2026 2019 2022 2016 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Umbilical Cord-Derived Mesenchymal Stem Cell-Derived Exosomal MicroRNAs Suppress Myofibroblast Differentiation by Inhibiting the Transforming Growth Factor-β/SMAD2 Pathway During Wound Healing
    2016 455 citations Shuo Fang, Chao Yang et al. profile →

Peers

Xin Xing
Fang Gao China
Yi Cheng China
Hye Young Choi South Korea
Xiaofei Deng China
Mingzi Zhang China
Wuquan Deng China
Huanwen Chen United States
Yili Fu China
Fang Gao China
Xin Xing
Citations per year, relative to Xin Xing Xin Xing (= 1×) peers Fang Gao

Countries citing papers authored by Xin Xing

Since Specialization
Citations

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

Fields of papers citing papers by Xin Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xin Xing

This figure shows the co-authorship network connecting the top 25 collaborators of Xin Xing. A scholar is included among the top collaborators of Xin Xing 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 Xin Xing. Xin Xing 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.
Chang, Ya‐Hsuan, Xin Xing, Anna Chen, et al.. (2025). Ketogenic Diet Modulates Gut Microbiota–Brain Metabolite Axis in a Sex‐ and Genotype‐Specific Manner in  APOE4 Mice. Journal of Neurochemistry. 169(9). e70216–e70216.
2.
Kuang, Yanbin, et al.. (2025). Applications of deep learning‐based resolution‐enhanced seismic data in fault identification. Geophysical Prospecting. 73(2). 523–542. 1 indexed citations
3.
Xing, Xin, He-Li Xu, Nan Bao, et al.. (2024). Non-invasive prediction of human embryonic ploidy using artificial intelligence: a systematic review and meta-analysis. EClinicalMedicine. 77. 102897–102897. 2 indexed citations
4.
Xing, Xin, Stefan J. Green, David Q. Beversdorf, et al.. (2024). Short‐term Sirolimus Treatment Restores Hippocampus and Caudate Volumes and Global Cerebral Blood Flow in Asymptomatic APOE4 Carriers Compared with Non‐carriers. Alzheimer s & Dementia. 20(S9). 1 indexed citations
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Hammond, Tyler C., Stefan J. Green, George E. Chlipala, et al.. (2023). Gut microbiome association with brain imaging markers, APOE genotype, calcium and vegetable intakes, and obesity in healthy aging adults. Frontiers in Aging Neuroscience. 15. 1227203–1227203. 10 indexed citations
8.
Chang, Ya‐Hsuan, Lucille M. Yanckello, George E. Chlipala, et al.. (2023). Prebiotic inulin enhances gut microbial metabolism and anti-inflammation in apolipoprotein E4 mice with sex-specific implications. Scientific Reports. 13(1). 15116–15116. 10 indexed citations
9.
Xing, Xin, et al.. (2023). Self-Supervised Learning Application on COVID-19 Chest X-ray Image Classification Using Masked AutoEncoder. Bioengineering. 10(8). 901–901. 10 indexed citations
10.
Xing, Xin, et al.. (2022). Association of selenium and cadmium with heart failure and mortality based on the National Health and Nutrition Examination Survey. Journal of Human Nutrition and Dietetics. 36(4). 1496–1506. 10 indexed citations
11.
Xing, Xin, et al.. (2022). Advit: Vision Transformer On Multi-Modality Pet Images For Alzheimer Disease Diagnosis. 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). 1–4. 30 indexed citations
12.
Yanckello, Lucille M., Ya‐Hsuan Chang, George E. Chlipala, et al.. (2022). Inulin supplementation prior to mild traumatic brain injury mitigates gut dysbiosis, and brain vascular and white matter deficits in mice. PubMed. 1. 8 indexed citations
13.
Hammond, Tyler C., Xin Xing, Chris Wang, et al.. (2020). β-amyloid and tau drive early Alzheimer’s disease decline while glucose hypometabolism drives late decline. UKnowledge (University of Kentucky). 2 indexed citations
14.
Xing, Xin, et al.. (2020). Cold exposure increased hypothalamic orexigenic neuropeptides but not food intake in fattening Daurian ground squirrels. Zoology. 143. 125834–125834. 1 indexed citations
15.
Zhang, Yuanzheng, Dan Li, Shuo Fang, et al.. (2019). Stimulatory effect of engineered three-layer adipose tissue-derived stem cells sheet in atelocollagen matrix on wound healing in a mouse model of radiation-induced skin injury. Journal of Biomaterials Applications. 34(4). 498–508. 12 indexed citations
16.
Liang, Gongbo, et al.. (2019). Joint 2D-3D Breast Cancer Classification. 692–696. 25 indexed citations
17.
Xing, Xin, et al.. (2016). Leptin regulates energy intake but fails to facilitate hibernation in fattening Daurian ground squirrels (Spermophilus dauricus). Journal of Thermal Biology. 57. 35–43. 5 indexed citations
18.
Xing, Xin, Ming Yang, & Dehua Wang. (2015). The expression of leptin, hypothalamic neuropeptides and UCP1 before, during and after fattening in the Daurian ground squirrel (Spermophilus dauricus). Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology. 184. 105–112. 11 indexed citations
19.
Yang, Chao, Peipei Zhang, & Xin Xing. (2013). Tear Trough and Palpebromalar Groove in Young versus Elderly Adults. Plastic & Reconstructive Surgery. 132(4). 796–808. 39 indexed citations
20.
Xing, Xin, An‐Jing Ren, Xing Zheng, et al.. (2009). Disturbance of circulating ghrelin and obestatin in chronic heart failure patients especially in those with cachexia. Peptides. 30(12). 2281–2285. 32 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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