Hongyu Kang

636 total citations
15 papers, 160 citations indexed

About

Hongyu Kang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Hongyu Kang has authored 15 papers receiving a total of 160 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Computational Theory and Mathematics and 3 papers in Artificial Intelligence. Recurrent topics in Hongyu Kang's work include Biomedical Text Mining and Ontologies (4 papers), Computational Drug Discovery Methods (4 papers) and Bioinformatics and Genomic Networks (3 papers). Hongyu Kang is often cited by papers focused on Biomedical Text Mining and Ontologies (4 papers), Computational Drug Discovery Methods (4 papers) and Bioinformatics and Genomic Networks (3 papers). Hongyu Kang collaborates with scholars based in China, United States and Taiwan. Hongyu Kang's co-authors include Jiao Li, De-Nian Yang, Wen-Tsuen Chen, Shan-Hsiang Shen, Jian-Jhih Kuo, Ming‐Jer Tsai, Si Zheng, Li Hou, Qin Li and Zaichao Zhang and has published in prestigious journals such as Nucleic Acids Research, Scientific Reports and Molecules.

In The Last Decade

Hongyu Kang

15 papers receiving 159 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hongyu Kang China	8	48	47	26	20	18	15	160
Christian Hundt Germany	10	72 1.5×	46 1.0×	21 0.8×	60 3.0×	8 0.4×	26	232
John D. Eblen United States	5	47 1.0×	17 0.4×	27 1.0×	26 1.3×	6 0.3×	7	113
Shengjun Li China	7	76 1.6×	8 0.2×	12 0.5×	58 2.9×	51 2.8×	19	190
Hoa T. Vu United States	6	74 1.5×	25 0.5×	24 0.9×	28 1.4×	2 0.1×	16	188
Vida Ravanmehr United States	5	110 2.3×	15 0.3×	21 0.8×	57 2.9×	58 3.2×	15	168
Włodzimierz Bielecki Poland	8	58 1.2×	58 1.2×	18 0.7×	59 3.0×	6 0.3×	44	162
Gregory J. Puleo United States	8	86 1.8×	22 0.5×	69 2.7×	82 4.1×	11 0.6×	23	202
Sky Faber United States	5	31 0.6×	13 0.3×	11 0.4×	84 4.2×	15 0.8×	7	121
Florian Sikora France	7	30 0.6×	22 0.5×	53 2.0×	23 1.1×	7 0.4×	15	101
Toshiki Saitoh Japan	8	16 0.3×	40 0.9×	80 3.1×	48 2.4×	11 0.6×	26	129

Countries citing papers authored by Hongyu Kang

Since Specialization

Citations

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

Fields of papers citing papers by Hongyu Kang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongyu Kang

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

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

Topaz, Maxim, et al.. (2024). Developing a Personalized Meal Recommendation System for Chinese Older Adults: Observational Cohort Study. JMIR Formative Research. 8. e52170–e52170. 2 indexed citations

Zheng, Si, et al.. (2024). Deep multiple instance learning on heterogeneous graph for drug–disease association prediction. Computers in Biology and Medicine. 184. 109403–109403. 1 indexed citations

Kang, Hongyu, et al.. (2023). Drug–disease association prediction with literature based multi-feature fusion. Frontiers in Pharmacology. 14. 1205144–1205144. 14 indexed citations

Li, Jiao, et al.. (2023). Employing Molecular Conformations for Ligand-Based Virtual Screening with Equivariant Graph Neural Network and Deep Multiple Instance Learning. Molecules. 28(16). 5982–5982. 12 indexed citations

Kang, Hongyu, et al.. (2022). Prediction and risk assessment of sepsis-associated encephalopathy in ICU based on interpretable machine learning. Scientific Reports. 12(1). 22621–22621. 15 indexed citations

Liu, Jiping, Junying Shen, Yan Zhang, et al.. (2022). Large topological Hall effect and in situ observation of magnetic domain structures in the Mn2FeSn compound. Materials Today Physics. 29. 100871–100871. 1 indexed citations

Zheng, Si, et al.. (2022). MilGNet: A Multi-instance Learning-based Heterogeneous Graph Network for Drug repositioning. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 430–437. 8 indexed citations

Lu, Mingming, Yadong Zhang, Jialin Mai, et al.. (2022). TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies. Nucleic Acids Research. 51(D1). D1179–D1187. 33 indexed citations

Wang, Shunmin, et al.. (2021). Adversarial domain adaptation network for tumor image diagnosis. International Journal of Approximate Reasoning. 135. 38–52. 7 indexed citations

10.

Li, Xiaorui, et al.. (2020). Microscope images automatic focus algorithm based on eight-neighborhood operator and least square planar fitting. Optik. 206. 164232–164232. 9 indexed citations

11.

Kang, Hongyu, et al.. (2020). Building a Pharmacogenomics Knowledge Model Toward Precision Medicine: Case Study in Melanoma. JMIR Medical Informatics. 8(10). e20291–e20291. 2 indexed citations

12.

Hou, Li, et al.. (2018). Mining and standardizing chinese consumer health terms. BMC Medical Informatics and Decision Making. 18(S5). 120–120. 3 indexed citations

13.

Kuo, Jian-Jhih, Shan-Hsiang Shen, Hongyu Kang, et al.. (2017). Service chain embedding with maximum flow in software defined network and application to the next-generation cellular network architecture. 1–9. 47 indexed citations

14.

Li, Jiao, et al.. (2016). Identifying Scientific Project-generated Data Citation from Full-text Articles: An Investigation of TCGA Data Citation. Journal of Data and Information Science. 1(2). 32–44. 2 indexed citations

15.

Kang, Hongyu, et al.. (2014). Generalized additive models of hospital admissions with respiratory disease and meteorology. 315–318. 4 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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