World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
66
Citations
16864
World Ranking
2336
National Ranking
322

Biology and Biochemistry

D-Index
68
Citations
17252
World Ranking
7761
National Ranking
244

Overview

Xing Chen is affiliated with Jiangnan University in China and has an extensive publication record primarily in the fields of Biochemistry, Genetics and Molecular Biology, as well as Medicine. Their research focuses on molecular biology, cancer research, computational theory and mathematics, oncology, and molecular medicine.

The scientist's recent notable papers include:

  • Deep-belief network for predicting potential miRNA-disease associations, 2020, published in Briefings in Bioinformatics
  • Prediction of potential miRNA-disease associations based on stacked autoencoder, 2022, published in Briefings in Bioinformatics

Xing Chen has collaborated frequently with several researchers including Chun-Chun Wang, Guanghua Zhang, Feifan Hou, Lihong Peng, and Junfeng Zhu. These collaborations have contributed to a range of publications in prominent venues.

Their articles have appeared regularly in journals such as:

  • Briefings in Bioinformatics
  • Computers in Biology and Medicine
  • IEEE Journal of Biomedical and Health Informatics
  • International Journal of Biological Macromolecules
  • International Immunopharmacology

Xing Chen's research covers numerous main topics, particularly in areas involving computational and biological methods, including:

  • Computational Drug Discovery Methods
  • Bioinformatics and Genomic Networks
  • Cancer-related molecular mechanisms research
  • MicroRNA in disease regulation
  • Circular RNAs in diseases
  • Single-cell and spatial transcriptomics
  • Machine Learning in Bioinformatics

With a substantial number of publications, Xing Chen's work frequently explores the intersection of machine learning and bioinformatics to address complex biological and medical problems. They have contributed specifically to the study of microRNA associations with diseases and the computational modeling of drug-target interactions.

Best Publications

  • LncRNADisease: a database for long-non-coding RNA-associated diseases

    Geng Chen;Ziyun Wang;Dongqing Wang;Chengxiang Qiu

  • Drug–target interaction prediction: databases, web servers and computational models

    Xing Chen;Chenggang Clarence Yan;Xiaotian Zhang;Xu Zhang

  • Novel human lncRNA-disease association inference based on lncRNA expression profiles

    Xing Chen;Gui-Ying Yan

  • MicroRNAs and complex diseases: from experimental results to computational models.

    Xing Chen;Di Xie;Qi Zhao;Zhu-Hong You

  • Long non-coding RNAs and complex diseases: from experimental results to computational models

    Xing Chen;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You

  • Drug-target interaction prediction by random walk on the heterogeneous network.

    Xing Chen;Ming-Xi Liu;Gui-Ying Yan

  • RWRMDA: predicting novel human microRNA–disease associations

    Xing Chen;Ming-Xi Liu;Gui-Ying Yan

  • Predicting miRNA-disease association based on inductive matrix completion.

    Xing Chen;Lei Wang;Jia Qu;Na-Na Guan

  • Semi-supervised learning for potential human microRNA-disease associations inference

    Xing Chen;Gui-Ying Yan

  • PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction.

    Zhu-Hong You;Zhi-An Huang;Zexuan Zhu;Gui-Ying Yan

  • WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.

    Xing Chen;Chenggang Clarence Yan;Xu Zhang;Zhu Hong You

  • MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction.

    Xing Chen;Jun Yin;Jia Qu;Li Huang

  • The B-RafV600E inhibitor dabrafenib selectively inhibits RIP3 and alleviates acetaminophen-induced liver injury

    Li Jx;Feng Jm;Wang Y;Li Xh

  • BNPMDA: Bipartite Network Projection for MiRNA-Disease Association prediction.

    Xing Chen;Di Xie;Lei Wang;Qi Zhao

  • EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction.

    Xing Chen;Li Huang;Di Xie;Qi Zhao

  • NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning.

    Xing Chen;Biao Ren;Ming Chen;Quanxin Wang

  • Constructing lncRNA functional similarity network based on lncRNA-disease associations and disease semantic similarity

    Xing Chen;Chenggang Clarence Yan;Cai Luo;Wen Ji

  • A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases

    Xing Chen;Yu-An Huang;Zhu-Hong You;Gui-Ying Yan

  • HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction

    Xing Chen;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You

  • LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction.

    Xing Chen;Li Huang

Frequent Co-Authors

Zhu-Hong You
Zhu-Hong You Chinese Academy of Sciences
Jianqiang Li
Jianqiang Li Beijing University of Technology
Zexuan Zhu
Zexuan Zhu Shenzhen University
De-Shuang Huang
De-Shuang Huang Tongji University
Yongdong Zhang
Yongdong Zhang University of Science and Technology of China
Hui Liu
Hui Liu China University of Mining and Technology
Qionghai Dai
Qionghai Dai Tsinghua University
Keith C. C. Chan
Keith C. C. Chan Hong Kong Polytechnic University
Qinghua Cui
Qinghua Cui Peking University
Lixin Zhang
Lixin Zhang East China University of Science and Technology

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