Shao‐Ching Hung

511 total citations
18 papers, 392 citations indexed

About

Shao‐Ching Hung is a scholar working on Molecular Biology, Physiology and Epidemiology. According to data from OpenAlex, Shao‐Ching Hung has authored 18 papers receiving a total of 392 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Physiology and 5 papers in Epidemiology. Recurrent topics in Shao‐Ching Hung's work include Diet and metabolism studies (4 papers), Adipose Tissue and Metabolism (4 papers) and Adipokines, Inflammation, and Metabolic Diseases (4 papers). Shao‐Ching Hung is often cited by papers focused on Diet and metabolism studies (4 papers), Adipose Tissue and Metabolism (4 papers) and Adipokines, Inflammation, and Metabolic Diseases (4 papers). Shao‐Ching Hung collaborates with scholars based in United States, India and Hong Kong. Shao‐Ching Hung's co-authors include Scott A. Young, Sunney I. Chan, Marsha L. Langhorst, Glenn E. Bartley, Wallace Yokoyama, Wei Wang, Alexander V. Alekseyenko, Zhan Gao, Monika Bihan and Barbara A. Methé and has published in prestigious journals such as Journal of Biological Chemistry, Analytical Chemistry and Journal of Agricultural and Food Chemistry.

In The Last Decade

Shao‐Ching Hung

18 papers receiving 388 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shao‐Ching Hung United States 12 191 78 68 46 40 18 392
Qi Liang United States 6 365 1.9× 131 1.7× 76 1.1× 52 1.1× 35 0.9× 8 568
Elodie Quévrain France 11 254 1.3× 44 0.6× 80 1.2× 59 1.3× 33 0.8× 25 559
Rena Balzan Malta 11 303 1.6× 23 0.3× 39 0.6× 35 0.8× 37 0.9× 13 504
Morgan J. Cichon United States 13 147 0.8× 19 0.2× 60 0.9× 45 1.0× 38 0.9× 17 437
Allison K. Stewart United States 13 281 1.5× 34 0.4× 39 0.6× 63 1.4× 59 1.5× 19 557
Asahi Suzuki Japan 13 212 1.1× 30 0.4× 41 0.6× 31 0.7× 13 0.3× 26 512
Ana Martínez-del Campo United States 9 542 2.8× 189 2.4× 28 0.4× 49 1.1× 41 1.0× 10 666
Amit Kumar Singh India 15 250 1.3× 100 1.3× 120 1.8× 21 0.5× 8 0.2× 30 600
Yongwei Zhao China 17 316 1.7× 75 1.0× 52 0.8× 20 0.4× 16 0.4× 38 656
Akinobu Matsuyama Japan 15 697 3.6× 28 0.4× 29 0.4× 124 2.7× 21 0.5× 24 814

Countries citing papers authored by Shao‐Ching Hung

Since Specialization
Citations

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

Fields of papers citing papers by Shao‐Ching Hung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shao‐Ching Hung. 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 Shao‐Ching Hung. The network helps show where Shao‐Ching Hung may publish in the future.

Co-authorship network of co-authors of Shao‐Ching Hung

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

All Works

18 of 18 papers shown
1.
Dementiev, Alexey, Anand Sitaram, Timothy Hey, et al.. (2016). The pesticidal Cry6Aa toxin from Bacillus thuringiensis is structurally similar to HlyE-family alpha pore-forming toxins. BMC Biology. 14(1). 71–71. 33 indexed citations
2.
Cox, Laura M., Ilseung Cho, Scott A. Young, et al.. (2012). The nonfermentable dietary fiber hydroxypropyl methylcellulose modulates intestinal microbiota. The FASEB Journal. 27(2). 692–702. 82 indexed citations
3.
Hung, Shao‐Ching, Wallace Yokoyama, Hyunsook Kim, et al.. (2012). Effects of Cationic Hydroxyethyl Cellulose on Dyslipidemia in Hamsters. Journal of Agricultural and Food Chemistry. 60(44). 11149–11156. 3 indexed citations
4.
Young, Scott A., et al.. (2011). Effects of cationic hydroxyethyl cellulose on glucose metabolism and obesity in a diet‐induced obesity mouse model. Journal of Diabetes. 4(1). 85–94. 9 indexed citations
5.
Hung, Shao‐Ching, et al.. (2011). Effect of hydroxypropyl methylcellulose on obesity and glucose metabolism in a diet-induced obesity mouse model. Journal of Diabetes. 3(2). 158–167. 17 indexed citations
6.
Yokoyama, Wallace, Yun‐Jeong Hong, Marsha L. Langhorst, et al.. (2011). Dietary Hydroxypropyl Methylcellulose Increases Excretion of Saturated and Trans Fats by Hamsters Fed Fast Food Diets. Journal of Agricultural and Food Chemistry. 59(20). 11249–11254. 14 indexed citations
7.
Bartley, Glenn E., Wallace Yokoyama, Scott A. Young, et al.. (2010). Hypocholesterolemic Effects of Hydroxypropyl Methylcellulose Are Mediated by Altered Gene Expression in Hepatic Bile and Cholesterol Pathways of Male Hamsters. Journal of Nutrition. 140(7). 1255–1260. 54 indexed citations
8.
Langhorst, Marsha L., et al.. (2010). Determination of F2-Isoprostanes in Urine by Online Solid Phase Extraction Coupled to Liquid Chromatography with Tandem Mass Spectrometry. Journal of Agricultural and Food Chemistry. 58(11). 6614–6620. 21 indexed citations
9.
Hung, Shao‐Ching, et al.. (2009). Dietary fiber improves lipid homeostasis and modulates adipocytokines in hamsters. Journal of Diabetes. 1(3). 194–206. 21 indexed citations
10.
Young, Scott A., Samir Julka, Glenn E. Bartley, et al.. (2009). Quantification of the Sulfated Cholecystokinin CCK-8 in Hamster Plasma Using Immunoprecipitation Liquid Chromatography-Mass Spectrometry/Mass Spectrometry. Analytical Chemistry. 81(21). 9120–9128. 5 indexed citations
11.
Seidel, Shawn D., Shao‐Ching Hung, Hayato Kan, & B. Bhaskar Gollapudi. (2006). Background Gene Expression in Rat Kidney: Influence of Strain, Gender, and Diet. Toxicological Sciences. 94(1). 226–233. 9 indexed citations
12.
Hung, Shao‐Ching, Nei‐Li Chan, Kelvin H.‐C. Chen, Steve S.‐F. Yu, & Sunney I. Chan. (2004). The Catalytic Copper Clusters of the Particulate Methane Monooxygenase from Methanotrophic Bacteria: Electron Paramagnetic Resonance Spectral Simulations. Journal of the Chinese Chemical Society. 51(5B). 1229–1244. 29 indexed citations
13.
Hung, Shao‐Ching, et al.. (2001). Structural, Magnetic and Catalytic Properties of a Self-Recognized μ-Oxo-Bridged Diiron(III) Bis(benzimidazole) Complex. Inorganic Chemistry. 40(16). 4036–4039. 13 indexed citations
14.
Hung, Shao‐Ching, et al.. (2000). ESEEM studies of succinate:ubiquinone reductase from Paracoccus denitrificans. JBIC Journal of Biological Inorganic Chemistry. 5(5). 593–602. 8 indexed citations
15.
16.
Kwok, Wai-Him, Maosheng Duan, Shao‐Ching Hung, et al.. (2000). Synthesis and Characterization of the Dimethyl-Substituted Bisbenzimidazole Ligand and Its Manganese Complex. Inorganic Chemistry. 39(11). 2367–2376. 10 indexed citations
17.
Hung, Shao‐Ching, et al.. (1999). Membrane Lysis by the Antibacterial Peptides Cecropins B1 and B3: A Spin-Label Electron Spin Resonance Study on Phospholipid Bilayers. Biophysical Journal. 77(6). 3120–3133. 30 indexed citations
18.
Waldeck, A. Reginald, Michael H. B. Stowell, Hung Kay Lee, et al.. (1997). Electron Paramagnetic Resonance Studies of Succinate:Ubiquinone Oxidoreductase from Paracoccus denitrificans. Journal of Biological Chemistry. 272(31). 19373–19382. 19 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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