Yulian Ding

622 total citations
23 papers, 439 citations indexed

About

Yulian Ding is a scholar working on Molecular Biology, Cancer Research and Computational Theory and Mathematics. According to data from OpenAlex, Yulian Ding has authored 23 papers receiving a total of 439 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 10 papers in Cancer Research and 7 papers in Computational Theory and Mathematics. Recurrent topics in Yulian Ding's work include MicroRNA in disease regulation (9 papers), Cancer-related molecular mechanisms research (8 papers) and Computational Drug Discovery Methods (7 papers). Yulian Ding is often cited by papers focused on MicroRNA in disease regulation (9 papers), Cancer-related molecular mechanisms research (8 papers) and Computational Drug Discovery Methods (7 papers). Yulian Ding collaborates with scholars based in Canada, China and United States. Yulian Ding's co-authors include Xiujuan Lei, Fang‐Xiang Wu, Bo Liao, Ping Luo, Hamido Fujita, Aidong Zhang, Minghan Fu, Bolin Chen, S. Austin Hammond and Patricia A. Thibault and has published in prestigious journals such as Nature Communications, BMC Genomics and Knowledge-Based Systems.

In The Last Decade

Yulian Ding

21 papers receiving 432 citations

Peers

Yulian Ding

CTM

CSE

Bingbo Wang China

Su-Ping Deng China

Ping Luo Canada

Laura Cantini France

Jiancheng Zhong China

Xiwei Tang China

Yanping Wu China

Chatchawit Aporntewan Thailand

Xiangtao Li China

Huang Yi-ran China

Bingbo Wang China

Yulian Ding

378 ×1.1

147 ×0.8

77 ×1.0

CTM

35 ×0.6

12 ×0.6

CSE

Citations per year, relative to Yulian Ding Yulian Ding (= 1×) peers Bingbo Wang

Countries citing papers authored by Yulian Ding

Since Specialization

Citations

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

Fields of papers citing papers by Yulian Ding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yulian Ding

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

Ding, Yulian, Yi Pan, C. Ronald Geyer, et al.. (2025). Unraveling bladder cancer-related circRNA biomarkers: a hybrid model combining deep learning and statistics. Health Information Science and Systems. 13(1). 53–53. 1 indexed citations

Hou, Zhanwei, et al.. (2025). MEGDTA: multi-modal drug-target affinity prediction based on protein three-dimensional structure and ensemble graph neural network. BMC Genomics. 26(1). 738–738. 1 indexed citations

Liu, Yajun, Fan Zhang, Yulian Ding, et al.. (2024). MRDPDA: A multi‐Laplacian regularized deepFM model for predicting piRNA‐disease associations. Journal of Cellular and Molecular Medicine. 28(17). e70046–e70046. 2 indexed citations

Ding, Yulian, Andrew Freywald, Yi Pan, et al.. (2024). Systematic Comparison of CRISPR and shRNA Screens to Identify Essential Genes Using a Graph-Based Unsupervised Learning Model. Cells. 13(19). 1653–1653. 1 indexed citations

Li, Jiawei, et al.. (2024). scCADE: A Superior Tool for Predicting Perturbation Responses in Single-Cell Gene Expression Using Contrastive Learning and Attention Mechanisms. 441–444.

Salapa, Hannah E., Patricia A. Thibault, Yulian Ding, et al.. (2024). hnRNP A1 dysfunction alters RNA splicing and drives neurodegeneration in multiple sclerosis (MS). Nature Communications. 15(1). 356–356. 26 indexed citations

Ding, Yulian, Minghan Fu, Ping Luo, & Fang‐Xiang Wu. (2023). Network Learning for Biomarker Discovery. 51–65. 25 indexed citations

Ding, Yulian, Xiujuan Lei, Bo Liao, & Fang‐Xiang Wu. (2023). Biomarker Identification via a Factorization Machine-Based Neural Network With Binary Pairwise Encoding. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(3). 2136–2146. 5 indexed citations

Ding, Yulian, Xiujuan Lei, Bo Liao, & Fang‐Xiang Wu. (2022). MLRDFM: a multi-view Laplacian regularized DeepFM model for predicting miRNA-disease associations. Briefings in Bioinformatics. 23(3). 23 indexed citations

10.

Liu, Yajun, Yulian Ding, Aimin Li, et al.. (2022). Prediction of exosomal piRNAs based on deep learning for sequence embedding with attention mechanism. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 158–161. 2 indexed citations

11.

Ding, Yulian, et al.. (2022). Unseen Epitope-TCR Interaction Prediction based on Amino Acid Physicochemical Properties. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 3122–3129.

12.

Ding, Yulian, et al.. (2021). Human Protein Complex-Based Drug Signatures for Personalized Cancer Medicine. IEEE Journal of Biomedical and Health Informatics. 25(11). 4079–4088. 2 indexed citations

13.

Ding, Yulian, Xiujuan Lei, Bo Liao, & Fang‐Xiang Wu. (2021). Machine learning approaches for predicting biomolecule–disease associations. Briefings in Functional Genomics. 20(4). 273–287. 14 indexed citations

14.

Wang, Fei, Yulian Ding, Xiujuan Lei, Bo Liao, & Fang‐Xiang Wu. (2021). Machine Learning and Deep Learning Strategies in Drug Repositioning. Current Bioinformatics. 17(3). 217–237. 6 indexed citations

15.

Ding, Yulian, et al.. (2020). Variational graph auto-encoders for miRNA-disease association prediction. Methods. 192. 25–34. 74 indexed citations

16.

Ding, Yulian, Bolin Chen, Xiujuan Lei, Bo Liao, & Fang‐Xiang Wu. (2020). Predicting novel CircRNA-disease associations based on random walk and logistic regression model. Computational Biology and Chemistry. 87. 107287–107287. 29 indexed citations

17.

Ding, Yulian, et al.. (2020). Identifying Gene Signatures for Cancer Drug Repositioning Based on Sample Clustering. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(2). 953–965. 7 indexed citations

18.

Ding, Yulian, et al.. (2020). Deep belief network–Based Matrix Factorization Model for MicroRNA-Disease Associations Prediction. Evolutionary Bioinformatics. 16. 1612666011–1612666011. 17 indexed citations

19.

Luo, Ping, Yulian Ding, Xiujuan Lei, & Fang‐Xiang Wu. (2019). deepDriver: Predicting Cancer Driver Genes Based on Somatic Mutations Using Deep Convolutional Neural Networks. Frontiers in Genetics. 10. 13–13. 77 indexed citations

20.

Lei, Xiujuan, Yulian Ding, Hamido Fujita, & Aidong Zhang. (2016). Identification of dynamic protein complexes based on fruit fly optimization algorithm. Knowledge-Based Systems. 105. 270–277. 45 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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