Wuxia Fu

1.5k total citations · 1 hit paper
14 papers, 1.2k citations indexed

About

Wuxia Fu is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Immunology. According to data from OpenAlex, Wuxia Fu has authored 14 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Cardiology and Cardiovascular Medicine and 4 papers in Immunology. Recurrent topics in Wuxia Fu's work include Lipid metabolism and disorders (4 papers), RNA Research and Splicing (4 papers) and Aquaculture disease management and microbiota (3 papers). Wuxia Fu is often cited by papers focused on Lipid metabolism and disorders (4 papers), RNA Research and Splicing (4 papers) and Aquaculture disease management and microbiota (3 papers). Wuxia Fu collaborates with scholars based in United States, Switzerland and Spain. Wuxia Fu's co-authors include Rosanne M. Crooke, Richard Lee, Mark J. Graham, Brenda F. Baker, Richard S. Geary, Adam E. Mullick, Sunny C. Jiang, Sotirios Tsimikas, Joseph L. Witztum and Thomas A. Bell and has published in prestigious journals such as New England Journal of Medicine, Journal of the American College of Cardiology and Circulation Research.

In The Last Decade

Wuxia Fu

14 papers receiving 1.1k citations

Hit Papers

align trajectories

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.

Cardiovascular and Metabolic Effects of ANGPTL3 Antisense Oligonucleotides

2017 454 citations Mark J. Graham, Richard Lee et al. New England Journal of Medicine profile →

Peers

Wuxia Fu

CCM

SURGE

EDM

Jens‐Gerd Scharf Germany

Niels Nijstad Netherlands

Detlev Ameis Germany

Haihui Sheng China

Christopher C. Fraser United States

Federica Basso United States

Ming He China

Daniel Terreros United States

Ferdinand M. van’t Hooft Sweden

Kenneth L. Hoppe United States

Jens‐Gerd Scharf Germany

Wuxia Fu

122 ×0.3

CCM

203 ×0.5

SURGE

485 ×1.2

EDM

475 ×1.3

294 ×1.1

Citations per year, relative to Wuxia Fu Wuxia Fu (= 1×) peers Jens‐Gerd Scharf

Countries citing papers authored by Wuxia Fu

Since Specialization

Citations

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

Fields of papers citing papers by Wuxia Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wuxia Fu

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

All Works

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14 of 14 papers shown

Pirie, Elaine, Wuxia Fu, Shayoni Ray, et al.. (2019). Hybrid Mouse Diversity Panel Identifies Genetic Architecture Associated with the Acute Antisense Oligonucleotide-Mediated Inflammatory Response to a 2′- O -Methoxyethyl Antisense Oligonucleotide. Nucleic Acid Therapeutics. 29(5). 266–277. 5 indexed citations

Fu, Wuxia, Richard Lee, Elaine Pirie, et al.. (2019). 2143-P: GLP-1 Conjugation Enhances the Activity of Antisense Oligonucleotides Targeting Islet Amyloid Polypeptide (IAPP) or Kelch-Like ECH Associated Protein 1 (Keap1) in Isolated Pancreatic Islets. Diabetes. 68(Supplement_1). 1 indexed citations

Pirie, Elaine, Shayoni Ray, Calvin Pan, et al.. (2018). Mouse genome-wide association studies and systems genetics uncover the genetic architecture associated with hepatic pharmacokinetic and pharmacodynamic properties of a constrained ethyl antisense oligonucleotide targeting Malat1. PLoS Genetics. 14(10). e1007732–e1007732. 6 indexed citations

Graham, Mark J., Richard Lee, Teresa Brandt, et al.. (2017). Cardiovascular and Metabolic Effects of ANGPTL3 Antisense Oligonucleotides. New England Journal of Medicine. 377(3). 222–232. 454 indexed citations breakdown →

Bell, Thomas A., Mark J. Graham, Richard Lee, et al.. (2013). Antisense oligonucleotide inhibition of cholesteryl ester transfer protein enhances RCT in hyperlipidemic, CETP transgenic, LDLr-/- mice. Journal of Lipid Research. 54(10). 2647–2657. 16 indexed citations

Graham, Mark J., Richard Lee, Thomas A. Bell, et al.. (2013). Antisense Oligonucleotide Inhibition of Apolipoprotein C-III Reduces Plasma Triglycerides in Rodents, Nonhuman Primates, and Humans. Circulation Research. 112(11). 1479–1490. 297 indexed citations

Lee, Richard, Wuxia Fu, Mark J. Graham, et al.. (2012). Comparison of the pharmacological profiles of murine antisense oligonucleotides targeting apolipoprotein B and microsomal triglyceride transfer protein. Journal of Lipid Research. 54(3). 602–614. 31 indexed citations

Mullick, Adam E., Wuxia Fu, Mark J. Graham, et al.. (2011). Antisense oligonucleotide reduction of apoB-ameliorated atherosclerosis in LDL receptor-deficient mice. Journal of Lipid Research. 52(5). 885–896. 37 indexed citations

Merki, Esther, Mark J. Graham, Adam Taleb, et al.. (2011). Antisense Oligonucleotide Lowers Plasma Levels of Apolipoprotein (a) and Lipoprotein (a) in Transgenic Mice. Journal of the American College of Cardiology. 57(15). 1611–1621. 105 indexed citations

10.

Zhang, Min, Wuxia Fu, James C. Moore, et al.. (2008). Inhibition of Polysome Assembly Enhances Imatinib Activity against Chronic Myelogenous Leukemia and Overcomes Imatinib Resistance. Molecular and Cellular Biology. 28(20). 6496–6509. 48 indexed citations

11.

Maeda, Naoyoshi, Wuxia Fu, Aurora Ortı́n, M. De las Heras, & Hung Fan. (2005). Roles of the Ras-MEK-Mitogen-Activated Protein Kinase and Phosphatidylinositol 3-Kinase-Akt-mTOR Pathways in Jaagsiekte Sheep Retrovirus-Induced Transformation of Rodent Fibroblast and Epithelial Cell Lines. Journal of Virology. 79(7). 4440–4450. 58 indexed citations

12.

Jiang, Sunny C., Wuxia Fu, Chu Wu, & Jed A. Fuhrman. (2003). The Vertical Distribution and Diversity of Marine Bacteriophage at a Station off Southern California. Microbial Ecology. 45(4). 399–410. 27 indexed citations

13.

Jiang, Sunny C., Weiping Chu, & Wuxia Fu. (2003). Prevalence of Cholera Toxin Genes ( ctxA and zot ) among Non-O1/O139 Vibrio cholerae Strainsfrom Newport Bay,California. Applied and Environmental Microbiology. 69(12). 7541–7544. 26 indexed citations

14.

Jiang, Sunny C. & Wuxia Fu. (2001). Seasonal Abundance and Distribution of Vibrio cholerae in Coastal Waters Quantified by a 16S-23S Intergenic Spacer Probe. Microbial Ecology. 42(4). 540–548. 43 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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