Tonghai Jiang

1.0k total citations
36 papers, 705 citations indexed

About

Tonghai Jiang is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Tonghai Jiang has authored 36 papers receiving a total of 705 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 10 papers in Molecular Biology and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Tonghai Jiang's work include Natural Language Processing Techniques (9 papers), Machine Learning in Bioinformatics (8 papers) and Bioinformatics and Genomic Networks (6 papers). Tonghai Jiang is often cited by papers focused on Natural Language Processing Techniques (9 papers), Machine Learning in Bioinformatics (8 papers) and Bioinformatics and Genomic Networks (6 papers). Tonghai Jiang collaborates with scholars based in China, Netherlands and Germany. Tonghai Jiang's co-authors include Zhu‐Hong You, Xi Zhou, Hai-Cheng Yi, Yanbin Wang, Li Cheng, Li Xiao, Xiao Li, Zhan‐Heng Chen, Li Xiao and Liping Li and has published in prestigious journals such as International Journal of Molecular Sciences, IEEE Access and BMC Bioinformatics.

In The Last Decade

Tonghai Jiang

32 papers receiving 691 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tonghai Jiang China 11 476 150 95 76 59 36 705
Muhammad Tahir Pakistan 21 1.0k 2.2× 101 0.7× 202 2.1× 105 1.4× 9 0.2× 46 1.5k
Demi Guo United States 7 1.3k 2.6× 244 1.6× 279 2.9× 23 0.3× 29 0.5× 9 1.7k
Li Cheng China 14 307 0.6× 73 0.5× 155 1.6× 95 1.3× 248 4.2× 30 761
Yanbin Wang China 14 359 0.8× 140 0.9× 59 0.6× 47 0.6× 11 0.2× 41 522
Zaheer Ullah Khan China 16 460 1.0× 93 0.6× 148 1.6× 15 0.2× 85 1.4× 32 894
Shahid Akbar Pakistan 26 1.2k 2.6× 278 1.9× 237 2.5× 59 0.8× 33 0.6× 40 1.8k
Quang‐Thai Ho Taiwan 14 544 1.1× 49 0.3× 131 1.4× 46 0.6× 10 0.2× 18 794
Huang Cheng-bing China 4 192 0.4× 48 0.3× 56 0.6× 34 0.4× 11 0.2× 10 369
Brandon Malone United States 13 291 0.6× 22 0.1× 168 1.8× 55 0.7× 16 0.3× 29 605
Abhinav Kumar India 15 355 0.7× 58 0.4× 381 4.0× 9 0.1× 18 0.3× 38 955

Countries citing papers authored by Tonghai Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Tonghai Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tonghai Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Tonghai Jiang. A scholar is included among the top collaborators of Tonghai 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 Tonghai Jiang. Tonghai Jiang 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.
Yi, Hai-Cheng, Zhu‐Hong You, Lei Wang, et al.. (2021). In silico drug repositioning using deep learning and comprehensive similarity measures. BMC Bioinformatics. 22(S3). 293–293. 12 indexed citations
2.
Jiang, Tonghai, et al.. (2021). Improving Distant Supervised Relation Extraction with Noise Detection Strategy. Applied Sciences. 11(5). 2046–2046.
3.
Jiang, Tonghai, et al.. (2020). Variance error of multi-classification based anomaly detection for time series data. Journal of Computational Methods in Sciences and Engineering. 21(4). 875–890. 2 indexed citations
4.
Jiang, Tonghai, et al.. (2020). Modeling and reasoning of IoT architecture in semantic ontology dimension. Computer Communications. 153. 580–594. 24 indexed citations
5.
Yi, Hai-Cheng, Zhu‐Hong You, Xi Zhou, et al.. (2019). ACP-DL: A Deep Learning Long Short-Term Memory Model to Predict Anticancer Peptides Using High-Efficiency Feature Representation. Molecular Therapy — Nucleic Acids. 17. 1–9. 160 indexed citations
6.
Yi, Hai-Cheng, Zhu‐Hong You, Li Cheng, et al.. (2019). Learning distributed representations of RNA and protein sequences and its application for predicting lncRNA-protein interactions. Computational and Structural Biotechnology Journal. 18. 20–26. 32 indexed citations
7.
Wang, Yanbin, Zhu‐Hong You, Shan Yang, et al.. (2019). A High Efficient Biological Language Model for Predicting Protein–Protein Interactions. Cells. 8(2). 122–122. 63 indexed citations
8.
Yi, Hai-Cheng, Zhu‐Hong You, De-Shuang Huang, et al.. (2018). A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information. Molecular Therapy — Nucleic Acids. 11. 337–344. 96 indexed citations
9.
Wang, Yanbin, Zhu‐Hong You, Liping Li, et al.. (2018). Predicting Protein Interactions Using a Deep Learning Method‐Stacked Sparse Autoencoder Combined with a Probabilistic Classification Vector Machine. Complexity. 2018(1). 16 indexed citations
10.
Yang, Yating, et al.. (2018). A Neural Network Based Model for Loanword Identification in Uyghur. Language Resources and Evaluation. 3 indexed citations
11.
Yang, Yating, et al.. (2018). Toward Better Loanword Identification in Uyghur Using Cross-lingual Word Embeddings. International Conference on Computational Linguistics. 3027–3037. 3 indexed citations
12.
Wang, Yanbin, Zhu‐Hong You, Xiao Li, et al.. (2018). Prediction of protein self-interactions using stacked long short-term memory from protein sequences information. BMC Systems Biology. 12(S8). 129–129. 8 indexed citations
13.
Zhu, Zhengwei, et al.. (2018). A Type-Based Blocking Technique for Efficient Entity Resolution over Large-Scale Data. Journal of Sensors. 2018. 1–12. 3 indexed citations
14.
Zhao, Qinghua, et al.. (2018). LCM: A Latent Communities Model based Community Detection Algorithm. 19. 74–78. 1 indexed citations
15.
Wang, Yanbin, Zhu‐Hong You, Li Xiao, et al.. (2017). Predicting protein–protein interactions from protein sequences by a stacked sparse autoencoder deep neural network. Molecular BioSystems. 13(7). 1336–1344. 86 indexed citations
16.
Jiang, Tonghai, et al.. (2017). A Novel Data Integration Framework Based on Unified Concept Model. IEEE Access. 5. 5713–5722. 9 indexed citations
17.
Yang, Yating, et al.. (2016). Recurrent Neural Network Based Loanwords Identification in Uyghur.. Waseda University Repository (Waseda University). 209–217. 5 indexed citations
18.
Jiang, Tonghai, et al.. (2010). Medical image computing and computer-assisted intervention (MICCAI 2010) : 13th international conference, Beijing, China, September 20-24, 2010, proceedings, part I. TU/e Research Portal (Eindhoven University of Technology). 13. 7 indexed citations
19.
20.
Zhou, Debao, et al.. (2004). Research of Water Flooded Performance and Pattern in Horizontal Well With Bottom-Water Drive Reservoir. Canadian International Petroleum Conference. 6 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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