Chih-Hong Wang

675 total citations
26 papers, 490 citations indexed

About

Chih-Hong Wang is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Chih-Hong Wang has authored 26 papers receiving a total of 490 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cardiology and Cardiovascular Medicine, 5 papers in Molecular Biology and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Chih-Hong Wang's work include Distributed Sensor Networks and Detection Algorithms (4 papers), Energy Harvesting in Wireless Networks (3 papers) and Nitric Oxide and Endothelin Effects (3 papers). Chih-Hong Wang is often cited by papers focused on Distributed Sensor Networks and Detection Algorithms (4 papers), Energy Harvesting in Wireless Networks (3 papers) and Nitric Oxide and Endothelin Effects (3 papers). Chih-Hong Wang collaborates with scholars based in Taiwan, United States and Australia. Chih-Hong Wang's co-authors include Hao-Tien Liu, Chia‐Nan Wang, Subhrakanti Dey, Nobuyuki Takahashi, Hendra Susanto, Shey-Cherng Tzou, Yu-Jen Chen, Peï-Yu Wu, Sathyadevi Palanisamy and Yunming Wang and has published in prestigious journals such as Journal of Biological Chemistry, IEEE Transactions on Signal Processing and Biosensors and Bioelectronics.

In The Last Decade

Chih-Hong Wang

26 papers receiving 483 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chih-Hong Wang Taiwan 14 100 93 85 74 70 26 490
Mária Ďurišová Slovakia 15 66 0.7× 23 0.2× 147 1.7× 32 0.4× 79 1.1× 82 674
Yunjia Zhang China 13 11 0.1× 56 0.6× 146 1.7× 32 0.4× 9 0.1× 46 680
Jiří Kukačka Czechia 18 35 0.3× 21 0.2× 164 1.9× 10 0.1× 23 0.3× 64 870
Sarah Stryeck Austria 16 43 0.4× 154 1.7× 504 5.9× 24 0.3× 28 0.4× 30 853
Yong Zeng China 18 19 0.2× 18 0.2× 445 5.2× 20 0.3× 12 0.2× 64 916
Hak‐Soo Kim South Korea 13 22 0.2× 32 0.3× 188 2.2× 19 0.3× 45 0.6× 66 744
Bengt Hamrén Sweden 13 64 0.6× 49 0.5× 301 3.5× 152 2.1× 26 0.4× 41 958
J. P. Dickinson United Kingdom 12 46 0.5× 33 0.4× 126 1.5× 7 0.1× 8 0.1× 35 699
Yen‐Hao Chen Taiwan 17 15 0.1× 71 0.8× 211 2.5× 57 0.8× 30 0.4× 84 1.0k

Countries citing papers authored by Chih-Hong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Chih-Hong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chih-Hong Wang. 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 Chih-Hong Wang. The network helps show where Chih-Hong Wang may publish in the future.

Co-authorship network of co-authors of Chih-Hong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Chih-Hong Wang. A scholar is included among the top collaborators of Chih-Hong Wang 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 Chih-Hong Wang. Chih-Hong Wang 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.
Li, Xiao‐Chun, et al.. (2024). Deletion of AT1a receptors selectively in the proximal tubules of the kidney alters the hypotensive and natriuretic response to atrial natriuretic peptide via NPRA/cGMP/NO signaling. American Journal of Physiology-Renal Physiology. 327(6). F946–F956. 1 indexed citations
2.
Wang, Chih-Hong, et al.. (2023). Fatty acids and inflammatory stimuli induce expression of long-chain acyl-CoA synthetase 1 to promote lipid remodeling in diabetic kidney disease. Journal of Biological Chemistry. 300(1). 105502–105502. 6 indexed citations
3.
Sas, Kelli M., Chih-Hong Wang, Hongyu Zhang, et al.. (2021). Renin-angiotensin system inhibition reverses the altered triacylglycerol metabolic network in diabetic kidney disease. Metabolomics. 17(7). 65–65. 15 indexed citations
4.
5.
Wang, Chih-Hong. (2019). Inhibition of Renin Angiotensin System Improves Leptin and Insulin Sensitivity, but Causes Severe Anemia Due to Hypothyroidism. Carolina Digital Repository (University of North Carolina at Chapel Hill). 1 indexed citations
6.
Wang, Chih-Hong, et al.. (2017). Comparative microarray analyses of mono(2-ethylhexyl)phthalate impacts on fat cell bioenergetics and adipokine network. Cell Biology and Toxicology. 33(6). 511–526. 18 indexed citations
7.
Palanisamy, Sathyadevi, Peï-Yu Wu, Shou-Cheng Wu, et al.. (2017). In vitro and in vivo imaging of peroxynitrite by a ratiometric boronate-based fluorescent probe. Biosensors and Bioelectronics. 91. 849–856. 81 indexed citations
8.
Susanto, Hendra, et al.. (2016). Higher serum betatrophin level in type 2 diabetes subjects is associated with urinary albumin excretion and renal function. Cardiovascular Diabetology. 15(1). 3–3. 46 indexed citations
9.
Susanto, Hendra, et al.. (2016). Increased serum levels of betatrophin in pancreatic cancer-associated diabetes. Oncotarget. 7(27). 42330–42339. 6 indexed citations
10.
Chen, Jen‐Kun, Shin-E Wang, Yi‐Ming Shyr, et al.. (2016). Prorenin receptor acts as a potential molecular target for pancreatic ductal adenocarcinoma diagnosis. Oncotarget. 7(34). 55437–55448. 20 indexed citations
11.
Wu, Wan-Chen, et al.. (2016). Altered plasma acylcarnitine and amino acid profiles in type 2 diabetic kidney disease. Metabolomics. 12(6). 27 indexed citations
12.
Wang, Chia‐Nan, et al.. (2011). Assessment on intellectual capital management for Taiwanese pharmaceutical industry: Using GRA and MPI. AFRICAN JOURNAL OF BUSINESS MANAGEMENT. 5(7). 2950–2958. 17 indexed citations
13.
Wang, Chih-Hong & Subhrakanti Dey. (2011). Distortion outage minimization in Nakagami fading using limited feedback. EURASIP Journal on Advances in Signal Processing. 2011(1). 7 indexed citations
14.
Liu, Hao-Tien & Chih-Hong Wang. (2010). An advanced quality function deployment model using fuzzy analytic network process. Applied Mathematical Modelling. 34(11). 3333–3351. 49 indexed citations
15.
Wang, Chih-Hong, Tiffany L. Thai, Gunnar Boysen, et al.. (2010). Elevated tissue factor expression contributes to exacerbated diabetic nephropathy in mice lacking eNOS fed a high fat diet. Journal of Thrombosis and Haemostasis. 8(10). 2122–2132. 31 indexed citations
16.
Wang, Chih-Hong, Feng Li, & Nobuyuki Takahashi. (2010). The Renin Angiotensin System and the Metabolic Syndrome~!2010-02-12~!2010-04-19~!2010-06-25~!. 3(1). 1–13. 20 indexed citations
17.
Wang, Chih-Hong & Subhrakanti Dey. (2009). Distortion Outage Minimization in Rayleigh Fading Using Limited Feedback. 51. 1–8. 5 indexed citations
18.
Wang, Chih-Hong & Subhrakanti Dey. (2008). Power Allocation for Distortion Outage Minimization in Clustered Wireless Sensor Networks. 2634. 395–400. 6 indexed citations
19.
Wang, Chia‐Nan & Chih-Hong Wang. (2007). A simulated model for cycle time reduction by acquiring optimal lot size in semiconductor manufacturing. The International Journal of Advanced Manufacturing Technology. 34(9-10). 1008–1015. 26 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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