Qiguo Dai

913 total citations
24 papers, 670 citations indexed

About

Qiguo Dai is a scholar working on Molecular Biology, Cancer Research and Computational Theory and Mathematics. According to data from OpenAlex, Qiguo Dai has authored 24 papers receiving a total of 670 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 11 papers in Cancer Research and 6 papers in Computational Theory and Mathematics. Recurrent topics in Qiguo Dai's work include Cancer-related molecular mechanisms research (11 papers), Computational Drug Discovery Methods (6 papers) and Bioinformatics and Genomic Networks (6 papers). Qiguo Dai is often cited by papers focused on Cancer-related molecular mechanisms research (11 papers), Computational Drug Discovery Methods (6 papers) and Bioinformatics and Genomic Networks (6 papers). Qiguo Dai collaborates with scholars based in China and United States. Qiguo Dai's co-authors include Maozu Guo, Zhixia Teng, Ping Xuan, Jin Li, Yong Liu, Yufei Huang, Jinbao Li, Jian Ding, Yahong Guo and Ke Han and has published in prestigious journals such as Bioinformatics, PLoS ONE and Neurocomputing.

In The Last Decade

Qiguo Dai

24 papers receiving 665 citations

Peers

Qiguo Dai

CTM

CVPR

Leon Wong China

Guangyuan Fu China

Zhixia Teng China

Bingbo Wang China

Bihai Zhao China

Boya Ji China

Jiancheng Ni China

Xiao-Nan Fan China

Frédéric Lafitte Belgium

Linlin Zhuo China

Leon Wong China

Qiguo Dai

574 ×1.0

208 ×0.5

232 ×3.8

CTM

54 ×1.9

16 ×0.6

CVPR

Citations per year, relative to Qiguo Dai Qiguo Dai (= 1×) peers Leon Wong

Countries citing papers authored by Qiguo Dai

Since Specialization

Citations

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

Fields of papers citing papers by Qiguo Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiguo Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Qiguo Dai. A scholar is included among the top collaborators of Qiguo Dai 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 Qiguo Dai. Qiguo Dai 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

Zhao, Shuang, et al.. (2024). Drug Sensitivity Prediction Based on Multi-stage Multi-modal Drug Representation Learning. Interdisciplinary Sciences Computational Life Sciences. 17(2). 231–243. 3 indexed citations

Teng, Zhixia, et al.. (2023). Constructing discriminative feature space for LncRNA–protein interaction based on deep autoencoder and marginal fisher analysis. Computers in Biology and Medicine. 157. 106711–106711. 5 indexed citations

Tian, Shengwei, et al.. (2022). RLF-LPI: An ensemble learning framework using sequence information for predicting lncRNA-protein interaction based on AE-ResLSTM and fuzzy decision. Mathematical Biosciences & Engineering. 19(5). 4749–4764. 9 indexed citations

Tian, Zhen, et al.. (2022). MHADTI: predicting drug–target interactions via multiview heterogeneous information network embedding with hierarchical attention mechanisms. Briefings in Bioinformatics. 23(6). 20 indexed citations

Dai, Qiguo, et al.. (2021). Predicting RBP Binding Sites of RNA With High-Order Encoding Features and CNN-BLSTM Hybrid Model. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(4). 2409–2419. 5 indexed citations

Dai, Qiguo, et al.. (2021). Predicting miRNA-disease associations using an ensemble learning framework with resampling method. Briefings in Bioinformatics. 23(1). 36 indexed citations

Tian, Shengwei, et al.. (2020). AC-Caps: Attention Based Capsule Network for Predicting RBP Binding Sites of LncRNA. Interdisciplinary Sciences Computational Life Sciences. 12(4). 414–423. 14 indexed citations

Dai, Qiguo, et al.. (2020). A Stacked Ensemble Learning Framework with Heterogeneous Feature Combinations for Predicting ncRNA-Protein Interaction. 67–71. 4 indexed citations

Tian, Shengwei, et al.. (2020). MD-MLI: Prediction of miRNA–lncRNA Interaction by Using Multiple Features and Hierarchical Deep Learning. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(3). 1724–1733. 19 indexed citations

10.

Dai, Qiguo, et al.. (2019). Construction of Complex Features for Computational Predicting ncRNA-Protein Interaction. Frontiers in Genetics. 10. 18–18. 24 indexed citations

11.

Dai, Qiguo, et al.. (2016). EnPC: An Ensemble Clustering Framework for Detecting Protein Complexes in Protein-Protein Interaction Network. Current Proteomics. 13(2). 143–150. 2 indexed citations

12.

Li, Jin, Limei Wang, Maozu Guo, et al.. (2015). Mining disease genes using integrated protein–protein interaction and gene–gene co‐regulation information. FEBS Open Bio. 5(1). 251–256. 14 indexed citations

13.

Dai, Qiguo, et al.. (2014). A Least Square Method Based Model for Identifying Protein Complexes in Protein-Protein Interaction Network. BioMed Research International. 2014. 1–9. 4 indexed citations

14.

Dai, Qiguo, Maozu Guo, Xiaoyan Liu, Zhixia Teng, & Chunyu Wang. (2014). CPL: Detecting Protein Complexes by Propagating Labels on Protein-Protein Interaction Network. Journal of Computer Science and Technology. 29(6). 1083–1093. 1 indexed citations

15.

Teng, Zhixia, Maozu Guo, Qiguo Dai, et al.. (2014). Computational Prediction of Protein Function Based on Weighted Mapping of Domains and GO Terms. BioMed Research International. 2014. 1–9. 5 indexed citations

16.

Guo, Maozu, et al.. (2014). On Protein Complexes Identifying Algorithm Based on the Novel Modularity Function. 51(10). 2178. 1 indexed citations

17.

Xuan, Ping, Ke Han, Maozu Guo, et al.. (2013). Prediction of microRNAs Associated with Human Diseases Based on Weighted k Most Similar Neighbors. PLoS ONE. 8(8). e70204–e70204. 279 indexed citations

18.

Teng, Zhixia, Maozu Guo, Xiaoyan Liu, et al.. (2013). Measuring gene functional similarity based on group-wise comparison of GO terms. Bioinformatics. 29(11). 1424–1432. 81 indexed citations

19.

Xuan, Ping, Ke Han, Maozu Guo, et al.. (2013). Correction: Prediction of microRNAs Associated with Human Diseases Based on Weighted k Most Similar Neighbors. PLoS ONE. 8(8). 73 indexed citations

20.

Dai, Qiguo, Maozu Guo, Yang Liu, Xiaoyan Liu, & Ling Chen. (2013). MLPA: Detecting overlapping communities by multi-label propagation approach. 681–688. 11 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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