De Huang

802 total citations
20 papers, 588 citations indexed

About

De Huang is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, De Huang has authored 20 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Artificial Intelligence. Recurrent topics in De Huang's work include Machine Learning in Bioinformatics (6 papers), Bioinformatics and Genomic Networks (4 papers) and Protein Structure and Dynamics (3 papers). De Huang is often cited by papers focused on Machine Learning in Bioinformatics (6 papers), Bioinformatics and Genomic Networks (4 papers) and Protein Structure and Dynamics (3 papers). De Huang collaborates with scholars based in China, United States and Singapore. De Huang's co-authors include Guang-Bin Huang, Yuan Chang, Wenzheng Bao, Zheng Yin, Xiaobo Zhou, Zhu‐Hong You, Kyungsook Han, Jiming Liu, Yiu‐ming Cheung and Zhenhua Huang and has published in prestigious journals such as Bioinformatics, International Journal of Hydrogen Energy and BMC Bioinformatics.

In The Last Decade

De Huang

18 papers receiving 574 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
De Huang China	11	246	173	150	94	59	20	588
Tiantian He China	16	111 0.5×	261 1.5×	89 0.6×	77 0.8×	30 0.5×	51	555
Eghbal G. Mansoori Iran	12	106 0.4×	356 2.1×	120 0.8×	104 1.1×	33 0.6×	50	571
Yifan Wu China	12	149 0.6×	118 0.7×	191 1.3×	114 1.2×	13 0.2×	51	491
Siyuan Shen China	9	91 0.4×	52 0.3×	180 1.2×	103 1.1×	12 0.2×	31	543
Lulu Zhang China	9	134 0.5×	82 0.5×	204 1.4×	78 0.8×	32 0.5×	30	583
András Kocsor Hungary	12	153 0.6×	327 1.9×	155 1.0×	38 0.4×	59 1.0×	47	609
Jinfeng Pan China	12	146 0.6×	67 0.4×	128 0.9×	46 0.5×	39 0.7×	41	372
Mark Junjie Li China	11	108 0.4×	301 1.7×	148 1.0×	47 0.5×	20 0.3×	26	596
Jiaxu Leng China	14	58 0.2×	177 1.0×	465 3.1×	48 0.5×	17 0.3×	62	743
Andrej Gisbrecht Germany	11	63 0.3×	219 1.3×	204 1.4×	22 0.2×	38 0.6×	27	494

Countries citing papers authored by De Huang

Since Specialization

Citations

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

Fields of papers citing papers by De Huang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of De Huang

This figure shows the co-authorship network connecting the top 25 collaborators of De Huang. A scholar is included among the top collaborators of De 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 De Huang. De Huang 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:

20 of 20 papers shown

Liu, Yonghong, et al.. (2025). Experimental study on the efficiency of calcium lignosulfonate-modified red clay for radon mitigation. Journal of Radioanalytical and Nuclear Chemistry. 334(4). 2861–2874. 1 indexed citations

Hong, Changshou, et al.. (2025). Scenario analysis of radon attenuation efficacy of earthen cover for uranium mill tailings impoundment driven by dry and wet cycles. Nuclear Engineering and Technology. 57(11). 103755–103755.

Liu, Yonghong, et al.. (2024). Manipulating cathode composition to enhance performance of proton-conducting solid oxide fuel cells through indium doping. International Journal of Hydrogen Energy. 78. 363–367. 1 indexed citations

Huang, De, et al.. (2023). An Adaptive Kalman Filter for Online Monitoring of Mine Wind Speed. Archives of Mining Sciences. 3 indexed citations

Wang, Meihua, et al.. (2023). Frequency and content dual stream network for image dehazing. Image and Vision Computing. 139. 104820–104820. 10 indexed citations

Huang, De, et al.. (2022). Stress Analysis of KDP Single Crystals Caused by Thermal Expansion Mismatch during Traditional Growth. Crystals. 12(9). 1323–1323. 1 indexed citations

Huang, De, Jian Liu, & Lijun Deng. (2020). A hybrid-encoding adaptive evolutionary strategy algorithm for windage alteration fault diagnosis. Process Safety and Environmental Protection. 136. 242–252. 27 indexed citations

Huang, De, et al.. (2020). A Multiobjective Optimization Model for Continuous Allocation of Emergency Rescue Materials. Mathematical Problems in Engineering. 2020. 1–15. 5 indexed citations

Bao, Wenzheng, Zhenhua Huang, Yuan Chang, & De Huang. (2017). Pupylation sites prediction with ensemble classification model. International Journal of Data Mining and Bioinformatics. 18(2). 91–91. 40 indexed citations

10.

Huang, De, Zhenhua Huang, Yuan Chang, & Wenzheng Bao. (2017). Pupylation sites prediction with ensemble classification model. International Journal of Data Mining and Bioinformatics. 18(2). 91–91. 29 indexed citations

11.

You, Zhu‐Hong, Zheng Yin, Kyungsook Han, De Huang, & Xiaobo Zhou. (2010). A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network. BMC Bioinformatics. 11(1). 343–343. 72 indexed citations

12.

Zhang, Guangzheng, et al.. (2005). Combining a binary input encoding scheme with RBFNN for globulin protein inter-residue contact map prediction. Pattern Recognition Letters. 26(10). 1543–1553. 12 indexed citations

13.

Huang, Guang-Bin, et al.. (2005). Fast Modular Network Implementation for Support Vector Machines. IEEE Transactions on Neural Networks. 16(6). 1651–1663. 39 indexed citations

14.

Zhu, Zhi, et al.. (2005). The comparative study between ELM and SVM on predicting the postoperative survival time of NSCLC patients. 18(5). 636–640. 1 indexed citations

15.

Huang, De, et al.. (2005). Optimisation of radial basis function classifiers using simulated annealing algorithm for cancer classification. Electronics Letters. 41(11). 630–632. 11 indexed citations

16.

Huang, De, et al.. (2005). Using FCMC, FVS, and PCA Techniques for Feature Extraction of Multispectral Images. IEEE Geoscience and Remote Sensing Letters. 2(2). 108–112. 58 indexed citations

17.

Zhang, Guangzheng, De Huang, Ying‐Hui Zhu, & Yubin Li. (2005). Improving protein secondary structure prediction by using the residue conformational classes. Pattern Recognition Letters. 26(15). 2346–2352. 6 indexed citations

18.

Huang, De. (2004). A Constructive Approach for Finding Arbitrary Roots of Polynomials by Neural Networks. IEEE Transactions on Neural Networks. 15(2). 477–491. 150 indexed citations

19.

Bailey, David, Rosaria Russo, De Huang, et al.. (2003). The binding interfacedatabase (BID): a compilationof amino acid hot spots in protein interfaces. Bioinformatics. 19(11). 1453–1454. 112 indexed citations

20.

Huang, De, et al.. (2003). Neural network based system for counting people. 3. 2197–2201. 10 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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