Mingjian Jiang

1.2k total citations · 1 hit paper
24 papers, 796 citations indexed

About

Mingjian Jiang is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Mingjian Jiang has authored 24 papers receiving a total of 796 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computational Theory and Mathematics, 14 papers in Molecular Biology and 9 papers in Materials Chemistry. Recurrent topics in Mingjian Jiang's work include Computational Drug Discovery Methods (15 papers), Protein Structure and Dynamics (10 papers) and Machine Learning in Materials Science (9 papers). Mingjian Jiang is often cited by papers focused on Computational Drug Discovery Methods (15 papers), Protein Structure and Dynamics (10 papers) and Machine Learning in Materials Science (9 papers). Mingjian Jiang collaborates with scholars based in China, United Kingdom and Brazil. Mingjian Jiang's co-authors include Shugang Zhang, Zhiqiang Wei, Shuang Wang, Xiaofeng Wang, Zhen Li, Zhen Li, Qing Yuan, Shuang Wang, Zhen Li and Shuang Wang and has published in prestigious journals such as International Journal of Molecular Sciences, Expert Systems with Applications and IEEE Access.

In The Last Decade

Mingjian Jiang

23 papers receiving 778 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning methods for molecular representation and property prediction

2022 145 citations Zhen Li, Mingjian Jiang et al. Drug Discovery Today profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mingjian Jiang China	13	616	555	308	63	41	24	796
Simon Johansson Sweden	8	487 0.8×	330 0.6×	404 1.3×	59 0.9×	29 0.7×	19	678
Ben Liao China	6	481 0.8×	350 0.6×	297 1.0×	117 1.9×	43 1.0×	10	678
Tri Minh Nguyen Australia	6	565 0.9×	581 1.0×	213 0.7×	38 0.6×	59 1.4×	12	772
Hang Le France	3	551 0.9×	525 0.9×	197 0.6×	100 1.6×	49 1.2×	7	697
Weihe Zhong China	12	485 0.8×	447 0.8×	224 0.7×	72 1.1×	40 1.0×	17	655
Amol Thakkar Switzerland	8	646 1.0×	420 0.8×	554 1.8×	79 1.3×	61 1.5×	15	923
Rishal Aggarwal India	6	498 0.8×	505 0.9×	274 0.9×	46 0.7×	58 1.4×	6	799
Kuzma Khrabrov United States	2	420 0.7×	328 0.6×	287 0.9×	56 0.9×	30 0.7×	4	605
Jaechang Lim South Korea	9	396 0.6×	354 0.6×	238 0.8×	36 0.6×	58 1.4×	21	610
Arthur Garon Austria	9	370 0.6×	280 0.5×	207 0.7×	65 1.0×	39 1.0×	14	594

Countries citing papers authored by Mingjian Jiang

Since Specialization

Citations

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

Fields of papers citing papers by Mingjian Jiang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingjian Jiang

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

All Works

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20 of 20 papers shown

Wang, Hongjie, et al.. (2025). A Meta-Reinforcement Learning-Based Poisoning Attack Framework Against Federated Learning. IEEE Access. 13. 28628–28644. 2 indexed citations

Ma, Teng, et al.. (2025). SeqMG-RPI: A Sequence-Based Framework Integrating Multi-Scale RNA Features and Protein Graphs for RNA-Protein Interaction Prediction. Journal of Chemical Information and Modeling. 65(9). 4698–4713.

Jiang, Mingjian, et al.. (2024). Unsupervised Domain Adaptation via Contrastive Learning and Complementary Region-Class Mixing. IEEE Access. 12. 193284–193298. 1 indexed citations

Jiang, Mingjian, et al.. (2023). Hierarchical Siamese network for real-time visual tracking. Expert Systems with Applications. 238. 121651–121651. 8 indexed citations

Li, Yuming, et al.. (2023). Research on Blast Furnace Tuyere Image Anomaly Detection, Based on the Local Channel Attention Residual Mechanism. Applied Sciences. 13(2). 802–802. 7 indexed citations

Jiang, Mingjian, et al.. (2023). A deep learning method for drug-target affinity prediction based on sequence interaction information mining. PeerJ. 11. e16625–e16625. 4 indexed citations

Li, Zhen, Mingjian Jiang, Shuang Wang, & Shugang Zhang. (2022). Deep learning methods for molecular representation and property prediction. Drug Discovery Today. 27(12). 103373–103373. 145 indexed citations breakdown →

Jiang, Mingjian, Shuang Wang, Shugang Zhang, et al.. (2022). Sequence-based drug-target affinity prediction using weighted graph neural networks. BMC Genomics. 23(1). 449–449. 39 indexed citations

Zhang, Shugang, Weigang Lu, Fei Yang, et al.. (2022). Computational analysis of arrhythmogenesis in KCNH2 T618I mutation-associated short QT syndrome and the pharmacological effects of quinidine and sotalol. npj Systems Biology and Applications. 8(1). 43–43. 5 indexed citations

10.

Yang, Lingzhi, et al.. (2022). Application of Efficient Channel Attention Residual Mechanism in Blast Furnace Tuyere Image Anomaly Detection. Applied Sciences. 12(15). 7823–7823. 5 indexed citations

11.

Zhang, Shugang, Zhen Li, Mingjian Jiang, et al.. (2022). Enhancing Protein Function Prediction Performance by Utilizing AlphaFold-Predicted Protein Structures. Journal of Chemical Information and Modeling. 62(17). 4008–4017. 39 indexed citations

12.

Zhang, Shugang, Mingjian Jiang, Shuang Wang, et al.. (2021). SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network. International Journal of Molecular Sciences. 22(16). 8993–8993. 44 indexed citations

13.

Wang, Shuang, Mingjian Jiang, Shugang Zhang, et al.. (2021). MCN-CPI: Multiscale Convolutional Network for Compound–Protein Interaction Prediction. Biomolecules. 11(8). 1119–1119. 28 indexed citations

14.

Wang, Shuang, Zhen Li, Shugang Zhang, et al.. (2020). Corrections to “Molecular Property Prediction Based on a Multichannel Substructure Graph”. IEEE Access. 8. 127968–127968. 2 indexed citations

15.

Zhang, Shugang, Weigang Lu, Zhen Li, et al.. (2020). Mechanisms Underlying Sulfur Dioxide Pollution Induced Ventricular Arrhythmia: A Simulation Study. 381–386. 4 indexed citations

16.

Jiang, Mingjian, Zhen Li, Shugang Zhang, et al.. (2020). Drug–target affinity prediction using graph neural network and contact maps. RSC Advances. 10(35). 20701–20712. 228 indexed citations

17.

Jiang, Mingjian, Zhiqiang Wei, Shugang Zhang, et al.. (2019). FRSite: Protein drug binding site prediction based on faster R–CNN. Journal of Molecular Graphics and Modelling. 93. 107454–107454. 21 indexed citations

18.

Jiang, Mingjian, et al.. (2019). A novel protein descriptor for the prediction of drug binding sites. BMC Bioinformatics. 20(1). 478–478. 23 indexed citations

19.

Yuan, Qing, Zhiqiang Wei, Mingjian Jiang, et al.. (2019). Toxicity Prediction Method Based on Multi-Channel Convolutional Neural Network. Molecules. 24(18). 3383–3383. 29 indexed citations

20.

Meng, Mei, et al.. (2019). Property Prediction of Molecules in Graph Convolutional Neural Network Expansion. 263–266. 7 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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