Xun Chi

706 total citations
11 papers, 527 citations indexed

About

Xun Chi is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism and Molecular Biology. According to data from OpenAlex, Xun Chi has authored 11 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cardiology and Cardiovascular Medicine, 5 papers in Endocrinology, Diabetes and Metabolism and 3 papers in Molecular Biology. Recurrent topics in Xun Chi's work include Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Lipid metabolism and disorders (5 papers) and Cholesterol and Lipid Metabolism (2 papers). Xun Chi is often cited by papers focused on Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Lipid metabolism and disorders (5 papers) and Cholesterol and Lipid Metabolism (2 papers). Xun Chi collaborates with scholars based in United States, China and Australia. Xun Chi's co-authors include Brandon S.J. Davies, Shwetha K. Shetty, Emily M. Cushing, Emily C. Britt, Ren Zhang, Matthew J. Potthoff, Quan Zhou, Autumn G. York, Kevin J. Williams and Viet L. Bui and has published in prestigious journals such as Journal of Biological Chemistry, Nature Immunology and PLoS ONE.

In The Last Decade

Xun Chi

11 papers receiving 526 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xun Chi United States	8	255	182	171	110	97	11	527
Lillemor Mattsson-Hultén Sweden	9	88 0.3×	121 0.7×	32 0.2×	58 0.5×	91 0.9×	12	372
Gregory R. Warnes United States	6	113 0.4×	162 0.9×	70 0.4×	62 0.6×	20 0.2×	10	387
Maria Cristina Procopio Italy	8	89 0.3×	127 0.7×	92 0.5×	24 0.2×	39 0.4×	15	393
Gustavo Augusto Ferreira Mota Brazil	11	210 0.8×	184 1.0×	49 0.3×	81 0.7×	15 0.2×	32	485
Hangxiang Zhang China	8	77 0.3×	157 0.9×	40 0.2×	45 0.4×	58 0.6×	10	380
Chia-Hua Wu Taiwan	8	129 0.5×	145 0.8×	92 0.5×	42 0.4×	21 0.2×	18	369
Rose M. Fields United States	11	71 0.3×	231 1.3×	258 1.5×	52 0.5×	41 0.4×	15	555
Mehdi Ramezani–Moghadam Australia	10	53 0.2×	121 0.7×	98 0.6×	33 0.3×	75 0.8×	11	610
Yongwen Zhou China	8	45 0.2×	121 0.7×	125 0.7×	36 0.3×	53 0.5×	25	371
Uddalak Majumdar United States	13	116 0.5×	247 1.4×	36 0.2×	40 0.4×	20 0.2×	31	494

Countries citing papers authored by Xun Chi

Since Specialization

Citations

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

Fields of papers citing papers by Xun Chi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xun Chi

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

All Works

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11 of 11 papers shown

Zhou, Quan, Autumn G. York, Kevin J. Williams, et al.. (2020). Toll-Like Receptors Induce Signal-Specific Reprogramming of the Macrophage Lipidome. Cell Metabolism. 32(1). 128–143.e5. 106 indexed citations

Zhou, Quan, Xun Chi, Wei Yuan Hsieh, et al.. (2020). Interferon-mediated reprogramming of membrane cholesterol to evade bacterial toxins. Nature Immunology. 21(7). 746–755. 61 indexed citations

Ferrari, Alessandra, Cuiwen He, John P. Kennelly, et al.. (2020). Aster Proteins Regulate the Accessible Cholesterol Pool in the Plasma Membrane. Molecular and Cellular Biology. 40(19). 47 indexed citations

Gai, Xiaosong, et al.. (2020). A study on the relationship between Job DemandControl-Support and Job Burnout of College English Teachers. 12. 33–38. 2 indexed citations

Cushing, Emily M., et al.. (2018). Novel GPIHBP1-independent pathway for clearance of plasma TGs in Angptl4−/−Gpihbp1−/− mice. Journal of Lipid Research. 59(7). 1230–1243. 7 indexed citations

Chi, Xun, Emily C. Britt, Shwetha K. Shetty, et al.. (2017). ANGPTL8 promotes the ability of ANGPTL3 to bind and inhibit lipoprotein lipase. Molecular Metabolism. 6(10). 1137–1149. 143 indexed citations

Cushing, Emily M., et al.. (2017). Angiopoietin-like 4 directs uptake of dietary fat away from adipose during fasting. Molecular Metabolism. 6(8). 809–818. 74 indexed citations

Davies, Brandon S.J., Xun Chi, Emily C. Britt, et al.. (2017). ANGPTL8 Promotes the Ability of ANGPTL3 to Inhibit Lipoprotein Lipase. The FASEB Journal. 31(S1). 1 indexed citations

Chi, Xun, et al.. (2015). Angiopoietin-like 4 Modifies the Interactions between Lipoprotein Lipase and Its Endothelial Cell Transporter GPIHBP1. Journal of Biological Chemistry. 290(19). 11865–11877. 51 indexed citations

10.

Zhao, Yuwei, et al.. (2013). Maritime Mobile Channel Transmission Model Based on ITM. Advances in intelligent systems research. 68. 15 indexed citations

11.

Yin, Jianhua, Yangyang Dong, Xun Chi, et al.. (2013). Expression of blaA Underlies Unexpected Ampicillin-Induced Cell Lysis of Shewanella oneidensis. PLoS ONE. 8(3). e60460–e60460. 20 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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