Hung-Jin Huang

2.5k total citations
40 papers, 519 citations indexed

About

Hung-Jin Huang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Astronomy and Astrophysics. According to data from OpenAlex, Hung-Jin Huang has authored 40 papers receiving a total of 519 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 8 papers in Computational Theory and Mathematics and 7 papers in Astronomy and Astrophysics. Recurrent topics in Hung-Jin Huang's work include Computational Drug Discovery Methods (8 papers), Galaxies: Formation, Evolution, Phenomena (7 papers) and Influenza Virus Research Studies (3 papers). Hung-Jin Huang is often cited by papers focused on Computational Drug Discovery Methods (8 papers), Galaxies: Formation, Evolution, Phenomena (7 papers) and Influenza Virus Research Studies (3 papers). Hung-Jin Huang collaborates with scholars based in Taiwan, United States and Japan. Hung-Jin Huang's co-authors include Calvin Yu‐Chian Chen, Su‐Sen Chang, Calvin Yu‐Chian Chen, Shan‐hui Hsu, Shih‐Ho Lin, Cheng-Chun Lee, Hsin‐Yi Chen, Yongjiang Wu, Yung‐An Tsou and Kuan‐Chung Chen and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Molecules and RSC Advances.

In The Last Decade

Hung-Jin Huang

37 papers receiving 509 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hung-Jin Huang Taiwan 12 182 111 57 55 51 40 519
Hyang Sook Chun South Korea 10 216 1.2× 16 0.1× 16 0.3× 39 0.7× 50 1.0× 19 575
Sheng Yao China 14 283 1.6× 84 0.8× 50 0.9× 53 1.0× 53 1.0× 37 641
Sneha B. Bansode India 11 170 0.9× 178 1.6× 44 0.8× 47 0.9× 60 1.2× 18 630
Satyavani Kaliamurthi China 16 294 1.6× 67 0.6× 53 0.9× 29 0.5× 32 0.6× 33 633
Xiaoran Ma China 14 289 1.6× 17 0.2× 13 0.2× 40 0.7× 36 0.7× 36 541
Guanyu Wang China 15 312 1.7× 183 1.6× 29 0.5× 21 0.4× 60 1.2× 58 768
Anchala Kumari India 14 227 1.2× 94 0.8× 45 0.8× 34 0.6× 28 0.5× 31 441
Inés Maestro Spain 10 234 1.3× 170 1.5× 82 1.4× 33 0.6× 26 0.5× 11 613
Tanuj Sharma India 16 184 1.0× 117 1.1× 107 1.9× 47 0.9× 17 0.3× 36 586

Countries citing papers authored by Hung-Jin Huang

Since Specialization
Citations

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

Fields of papers citing papers by Hung-Jin Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hung-Jin Huang. 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 Hung-Jin Huang. The network helps show where Hung-Jin Huang may publish in the future.

Co-authorship network of co-authors of Hung-Jin Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Hung-Jin Huang. A scholar is included among the top collaborators of Hung-Jin Huang 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 Hung-Jin Huang. Hung-Jin Huang 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.
Chiu, Hui‐Wen, et al.. (2025). Cilostazol attenuates vascular inflammation via the regulation of TICAM1/IRF3 signaling pathway. Biomedicine & Pharmacotherapy. 189. 118275–118275.
2.
Huang, Hung-Jin, et al.. (2025). Performance and development trends of ultrasound diagnostic systems in military settings: a review. The Ultrasound Journal. 17(1). 54–54.
3.
Huang, Hung-Jin, et al.. (2025). Repurposing of FDA-approved drugs by targeting SIRT2 to alleviate inflammatory response and kidney injury. European Journal of Pharmaceutical Sciences. 214. 107296–107296.
4.
Huang, Hung-Jin, Chu‐Lin Chou, Sandar Tin Tin, et al.. (2023). Currently Used Methods to Evaluate the Efficacy of Therapeutic Drugs and Kidney Safety. Biomolecules. 13(11). 1581–1581. 3 indexed citations
5.
Krause, E., et al.. (2023). Kinematic lensing inference – I. Characterizing shape noise with simulated analyses. Monthly Notices of the Royal Astronomical Society. 524(3). 3324–3334. 2 indexed citations
6.
Wong, Chui‐Wei, et al.. (2021). Engineered Bacteriorhodopsin May Induce Lung Cancer Cell Cycle Arrest and Suppress Their Proliferation and Migration. Molecules. 26(23). 7344–7344. 4 indexed citations
7.
Fang, Xiao, T. F. Eifler, Emmanuel Schaan, et al.. (2021). Cosmology from Clustering, Cosmic Shear, CMB Lensing, and Cross Correlations: Combining Rubin Observatory and Simons Observatory. arXiv (Cornell University). 15 indexed citations
8.
Chen, Hsin‐Yi, Jianqiang Chen, Junyan Li, et al.. (2019). Deep Learning and Random Forest Approach for Finding the Optimal Traditional Chinese Medicine Formula for Treatment of Alzheimer’s Disease. Journal of Chemical Information and Modeling. 59(4). 1605–1623. 33 indexed citations
9.
Huang, Hung-Jin, et al.. (2017). Network pharmacology-based approach of novel traditional Chinese medicine formula for treatment of acute skin inflammation in silico. Computational Biology and Chemistry. 71. 70–81. 28 indexed citations
10.
Huang, Hung-Jin, Cheng-Chun Lee, & Calvin Yu‐Chian Chen. (2014). Lead Discovery for Alzheimer’s Disease Related Target Protein RbAp48 from Traditional Chinese Medicine. BioMed Research International. 2014. 1–14. 10 indexed citations
11.
Huang, Hung-Jin, Hsin‐Yi Chen, Cheng-Chun Lee, & Calvin Yu‐Chian Chen. (2014). Computational Design of Apolipoprotein E4 Inhibitors for Alzheimer’s Disease Therapy from Traditional Chinese Medicine. BioMed Research International. 2014. 1–13. 12 indexed citations
12.
Chang, Pei-Chun, et al.. (2014). Treatment of Acute Lymphoblastic Leukemia from Traditional Chinese Medicine. Evidence-based Complementary and Alternative Medicine. 2014(1). 601064–601064. 7 indexed citations
13.
14.
Tsou, Yung‐An, et al.. (2014). Lead Screening for Chronic Obstructive Pulmonary Disease of IKK2 Inhibited by Traditional Chinese Medicine. Evidence-based Complementary and Alternative Medicine. 2014(1). 465025–465025. 9 indexed citations
15.
Lin, Yen‐Ting, et al.. (2014). Stellar mass assembly of brightest cluster galaxies at late times. Monthly Notices of the Royal Astronomical Society. 446(1). 1107–1114. 9 indexed citations
16.
17.
Chen, Kuen‐Bao, et al.. (2014). Lead Screening for HIV of C‐C Chemokine Receptor Type 5 Receptor Inhibited by Traditional Chinese Medicine. Evidence-based Complementary and Alternative Medicine. 2014(1). 313094–313094. 2 indexed citations
18.
Huang, Hung-Jin, et al.. (2014). Investigation of Anti‐Infection Mechanism of Lactoferricin and Splunc‐1. Evidence-based Complementary and Alternative Medicine. 2014(1). 907028–907028. 5 indexed citations
19.
Huang, Hung-Jin & Calvin Yu‐Chian Chen. (2013). A possible solution for hair loss by inhibiting corticotropin-releasing factor (CRF) receptor from traditional Chinese medicine. Journal of Biomolecular Structure and Dynamics. 32(10). 1613–1623. 3 indexed citations
20.
Chang, Su‐Sen, Hung-Jin Huang, & Calvin Yu‐Chian Chen. (2011). High performance screening, structural and molecular dynamics analysis to identify H1 inhibitors from TCM Database@Taiwan. Molecular BioSystems. 7(12). 3366–3374. 37 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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