Chao-Wu Xiao

962 total citations · 1 hit paper
24 papers, 768 citations indexed

About

Chao-Wu Xiao is a scholar working on Pathology and Forensic Medicine, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Chao-Wu Xiao has authored 24 papers receiving a total of 768 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Pathology and Forensic Medicine, 6 papers in Molecular Biology and 6 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Chao-Wu Xiao's work include Phytoestrogen effects and research (12 papers), Diet, Metabolism, and Disease (6 papers) and Protein Hydrolysis and Bioactive Peptides (5 papers). Chao-Wu Xiao is often cited by papers focused on Phytoestrogen effects and research (12 papers), Diet, Metabolism, and Disease (6 papers) and Protein Hydrolysis and Bioactive Peptides (5 papers). Chao-Wu Xiao collaborates with scholars based in Canada, China and Nigeria. Chao-Wu Xiao's co-authors include Cynthia Chatterjee, S. Gleddie, A.K. Goff, Jean Sirois, Carla M. Wood, Nora Lee, G. Sarwar Gilani, Jesse Bertinato, Yulong Yin and Xiaoxue Yuan and has published in prestigious journals such as PLoS ONE, Scientific Reports and The FASEB Journal.

In The Last Decade

Chao-Wu Xiao

24 papers receiving 747 citations

Hit Papers

Soybean Bioactive Peptide... 2018 2026 2020 2023 2018 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
Chao-Wu Xiao Canada 12 271 149 145 125 119 24 768
Huixin Yang China 20 429 1.6× 106 0.7× 32 0.2× 78 0.6× 65 0.5× 49 1.1k
Lijuan Bao China 16 501 1.8× 164 1.1× 40 0.3× 110 0.9× 188 1.6× 43 1.0k
Hasan Akşit Türkiye 17 135 0.5× 54 0.4× 79 0.5× 53 0.4× 74 0.6× 53 808
T. Mitsuhashi Japan 17 264 1.0× 108 0.7× 51 0.4× 132 1.1× 67 0.6× 37 1.1k
Okjin Kim South Korea 17 306 1.1× 85 0.6× 43 0.3× 76 0.6× 46 0.4× 105 1.0k
M. Frigg Switzerland 20 163 0.6× 139 0.9× 59 0.4× 133 1.1× 148 1.2× 54 1.4k
Yanfen Ma China 19 590 2.2× 214 1.4× 77 0.5× 92 0.7× 31 0.3× 66 1.2k
G. Kuhn Germany 17 206 0.8× 103 0.7× 156 1.1× 20 0.2× 51 0.4× 33 1.1k
N. Oksbjerg Denmark 28 450 1.7× 187 1.3× 40 0.3× 48 0.4× 112 0.9× 57 2.1k
Zhiyue Wang China 20 212 0.8× 45 0.3× 46 0.3× 43 0.3× 66 0.6× 106 1.0k

Countries citing papers authored by Chao-Wu Xiao

Since Specialization
Citations

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

Fields of papers citing papers by Chao-Wu Xiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chao-Wu Xiao

This figure shows the co-authorship network connecting the top 25 collaborators of Chao-Wu Xiao. A scholar is included among the top collaborators of Chao-Wu Xiao 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 Chao-Wu Xiao. Chao-Wu Xiao 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.
Xiao, Chao-Wu, et al.. (2024). Consumption of soya isoflavones improved polycystic ovary syndrome-associated metabolic disorders in a rat model. British Journal Of Nutrition. 132(4). 416–424. 1 indexed citations
2.
Xiao, Chao-Wu, et al.. (2022). Hypolipidemic Effects of Soy Protein and Isoflavones in the Prevention of Non-Alcoholic Fatty Liver Disease- A Review. Plant Foods for Human Nutrition. 77(3). 319–328. 11 indexed citations
4.
Xiao, Chao-Wu, Carla M. Wood, & Jesse Bertinato. (2018). Dietary supplementation with l-lysine affects body weight and blood hematological and biochemical parameters in rats. Molecular Biology Reports. 46(1). 433–442. 14 indexed citations
5.
Chatterjee, Cynthia, S. Gleddie, & Chao-Wu Xiao. (2018). Soybean Bioactive Peptides and Their Functional Properties. Nutrients. 10(9). 1211–1211. 382 indexed citations breakdown →
7.
Chatterjee, Cynthia, Jiajie Liu, Carla M. Wood, et al.. (2017). The α’ subunit of β-conglycinin and various glycinin subunits of soy are not required to modulate hepatic lipid metabolism in rats. European Journal of Nutrition. 57(3). 1157–1168. 10 indexed citations
8.
Xiao, Chao-Wu, Carla M. Wood, Eleonora Swist, et al.. (2016). Cardio-Metabolic Disease Risks and Their Associations with Circulating 25-Hydroxyvitamin D and Omega-3 Levels in South Asian and White Canadians. PLoS ONE. 11(1). e0147648–e0147648. 11 indexed citations
9.
Bertinato, Jesse, et al.. (2016). l -Lysine supplementation does not affect the bioavailability of copper or iron in rats. Journal of Trace Elements in Medicine and Biology. 38. 194–200. 10 indexed citations
10.
Jiang, Hongmei, Xiangjun Liao, Carla M. Wood, Chao-Wu Xiao, & Yong‐Lai Feng. (2016). A robust analytical method for measurement of phytoestrogens and related metabolites in serum with liquid chromatography tandem mass spectrometry. Journal of Chromatography B. 1012-1013. 106–112. 4 indexed citations
11.
Farmer, C., Patrick Robertson, Chao-Wu Xiao, C. Rehfeldt, & Claudia Kalbe. (2016). Exogenous genistein in late gestation: effects on fetal development and sow and piglet performance. animal. 10(9). 1423–1430. 13 indexed citations
12.
Benkhedda, Karima, et al.. (2015). A Systematic Review and Meta‐analysis of the Effects of Soy Products on Blood Cholesterol Levels. The FASEB Journal. 29(S1). 1 indexed citations
13.
Li, Lili, et al.. (2015). Dietary soy isoflavones differentially regulate expression of the lipid-metabolic genes in different white adipose tissues of the female Bama mini-pigs. Biochemical and Biophysical Research Communications. 461(1). 159–164. 11 indexed citations
14.
Zhang, Bin, Lili Li, Chao-Wu Xiao, et al.. (2015). Effect of Soyabean Isoflavones Exposure on Onset of Puberty, Serum Hormone Concentration and Gene Expression in Hypothalamus, Pituitary Gland and Ovary of Female Bama Miniature Pigs. Asian-Australasian Journal of Animal Sciences. 28(11). 1573–1582. 6 indexed citations
15.
Yuan, Xiaoxue, Bin Zhang, Lili Li, et al.. (2012). Effects of soybean isoflavones on reproductive parameters in Chinese mini-pig boars. Journal of Animal Science and Biotechnology. 3(1). 31–31. 23 indexed citations
16.
Li, L. L., Huansheng Yang, Xiaoxue Yuan, et al.. (2011). Regulation of soy isoflavones on weight gain and fat percentage: evaluation in a Chinese Guangxi minipig model. animal. 5(12). 1903–1908. 22 indexed citations
17.
Xiao, Chao-Wu, et al.. (2003). Progesterone-Modulated Induction of Apoptosis by Interferon-Tau in Cultured Epithelial Cells of Bovine Endometrium1. Biology of Reproduction. 68(2). 673–679. 28 indexed citations
18.
Xiao, Chao-Wu, Lei Jin, & Xin Zhao. (2001). Bovine casein peptides co-stimulate naive macrophages with lipopolysaccharide for proinflammatory cytokine production and nitric oxide release. Journal of the Science of Food and Agriculture. 81(3). 300–304. 5 indexed citations
19.
Xiao, Chao-Wu & A.K. Goff. (1999). Hormonal regulation of oestrogen and progesterone receptors in cultured bovine endometrial cells. Reproduction. 115(1). 101–109. 42 indexed citations
20.

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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