Xinnan Wu

721 total citations
17 papers, 534 citations indexed

About

Xinnan Wu is a scholar working on Molecular Biology, Animal Science and Zoology and Immunology. According to data from OpenAlex, Xinnan Wu has authored 17 papers receiving a total of 534 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Animal Science and Zoology and 3 papers in Immunology. Recurrent topics in Xinnan Wu's work include Meat and Animal Product Quality (4 papers), Extracellular vesicles in disease (3 papers) and Advanced Chemical Sensor Technologies (3 papers). Xinnan Wu is often cited by papers focused on Meat and Animal Product Quality (4 papers), Extracellular vesicles in disease (3 papers) and Advanced Chemical Sensor Technologies (3 papers). Xinnan Wu collaborates with scholars based in China, United States and Sweden. Xinnan Wu's co-authors include Qing Ji, Lihong Zhou, Qi Li, Qing Song, Dengyong Liu, Ruixiao Li, Bo Wang, Liu Yang, Hua Sui and Yan Wang and has published in prestigious journals such as Nature Communications, Food Chemistry and Sustainability.

In The Last Decade

Xinnan Wu

17 papers receiving 530 citations

Peers

Xinnan Wu
Xinnan Wu
Citations per year, relative to Xinnan Wu Xinnan Wu (= 1×) peers Sheng Huang

Countries citing papers authored by Xinnan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xinnan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinnan Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Xinnan Wu. A scholar is included among the top collaborators of Xinnan Wu 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 Xinnan Wu. Xinnan Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Wu, Xinnan, Yuan Wang, Guanghong Zhou, et al.. (2025). Transforming Food Consumer Analysis: The Role of Machine Learning in Food Consumer Demand 4.0. Journal of Future Foods. 1 indexed citations
2.
Wu, Xinnan, et al.. (2024). Insights on purchase intention of mutton shashlik - A survey of Chinese consumers based on fsQCA. Future Foods. 10. 100446–100446. 1 indexed citations
3.
Pu, Yunzhou, Haoze Li, Ling Li, et al.. (2024). Kaempferol inhibits colorectal cancer metastasis through circ_0000345 mediated JMJD2C/β-catenin signalling pathway. Phytomedicine. 128. 155261–155261. 19 indexed citations
4.
Hou, Xinxin, Yuanyuan Feng, Yingru Zhang, et al.. (2024). A chronic stress-induced microbiome perturbation, highly enriched in Ruminococcaceae_UCG-014, promotes colorectal cancer growth and metastasis. International Journal of Medical Sciences. 21(5). 882–895. 3 indexed citations
5.
Li, Ling, Yunzhou Pu, Haoze Li, et al.. (2024). Astragaloside IV inhibits colorectal cancer metastasis by reducing extracellular vesicles release and suppressing M2-type TAMs activation. Heliyon. 10(10). e31450–e31450. 11 indexed citations
8.
Wu, Xinnan, et al.. (2023). Identifying the quality characteristics of pork floss structure based on deep learning framework. Current Research in Food Science. 7. 100587–100587. 2 indexed citations
9.
Wu, Xinnan, et al.. (2023). Predicting VOCs content and roasting methods of lamb shashliks using deep learning combined with chemometrics and sensory evaluation. Food Chemistry X. 19. 100755–100755. 16 indexed citations
10.
11.
Song, Qing, Zhifen Han, Xinnan Wu, et al.. (2021). β-Arrestin1 Promotes Colorectal Cancer Metastasis Through GSK-3β/β-Catenin Signaling- Mediated Epithelial-to-Mesenchymal Transition. Frontiers in Cell and Developmental Biology. 9. 650067–650067. 11 indexed citations
12.
13.
Song, Qing, Liu Yang, Zhifen Han, et al.. (2020). Tanshinone IIA Inhibits Epithelial-to-Mesenchymal Transition Through Hindering β-Arrestin1 Mediated β-Catenin Signaling Pathway in Colorectal Cancer. Frontiers in Pharmacology. 11. 586616–586616. 14 indexed citations
14.
Ji, Qing, Lihong Zhou, Hua Sui, et al.. (2020). Primary tumors release ITGBL1-rich extracellular vesicles to promote distal metastatic tumor growth through fibroblast-niche formation. Nature Communications. 11(1). 1211–1211. 204 indexed citations
15.
Wu, Xinnan, Ruixiao Li, Qing Song, et al.. (2019). JMJD2C promotes colorectal cancer metastasis via regulating histone methylation of MALAT1 promoter and enhancing β-catenin signaling pathway. Journal of Experimental & Clinical Cancer Research. 38(1). 435–435. 57 indexed citations
16.
Wu, Xinnan, et al.. (2018). Antitumor Research of the Active Ingredients from Traditional Chinese Medical Plant Polygonum Cuspidatum. Evidence-based Complementary and Alternative Medicine. 2018(1). 27 indexed citations
17.
Cheng, Jiwei, Min Yao, Quangang Zhu, et al.. (2015). Silencing of stat4 gene inhibits cell proliferation and invasion of colorectal cancer cells.. PubMed. 29(1). 85–92. 27 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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