World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
7246
World Ranking
6596
National Ranking
2914

Overview

Jijun Tang is affiliated with the University of South Carolina in the United States. Their research spans the intersection of biochemistry, genetics, molecular biology, and computer science, with a focus on various aspects of bioinformatics and computational biology. The primary fields of study include Biochemistry, Genetics and Molecular Biology, as well as Computer Science.

The scientist's research subfields cover Molecular Biology, Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Theory and Mathematics, and Cancer Research. The main research topics include Machine Learning in Bioinformatics, RNA and protein synthesis mechanisms, Computational Drug Discovery Methods, Genomics and Phylogenetic Studies, Bioinformatics and Genomic Networks, Gene expression and cancer classification, and Advanced Neural Network Applications.

Jijun Tang has published extensively in a range of venues. Frequent publication venues include Briefings in Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, the 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Current Bioinformatics, and Applied Soft Computing.

Among selected recent papers are:

  • Identification of Drug-Target Interactions via Dual Laplacian Regularized Least Squares with Multiple Kernel Fusion, 2020, Knowledge-Based Systems
  • DeepAVP: A Dual-Channel Deep Neural Network for Identifying Variable-Length Antiviral Peptides, 2020, IEEE Journal of Biomedical and Health Informatics
  • A comprehensive overview and critical evaluation of gene regulatory network inference technologies, 2021, Briefings in Bioinformatics
  • Exploring associations of non-coding RNAs in human diseases via three-matrix factorization with hypergraph-regular terms on center kernel alignment, 2020, Briefings in Bioinformatics
  • A hybrid deep learning framework for gene regulatory network inference from single-cell transcriptomic data, 2021, Briefings in Bioinformatics

Jijun Tang collaborates frequently with other researchers. Notable co-authors include Fei Guo, Yijie Ding, Limin Jiang, Yan Guo, and Shiqiang Ma.

Best Publications

  • Local-DPP: An improved DNA-binding protein prediction method by exploring local evolutionary information

    Leyi Wei;Jijun Tang;Jijun Tang;Quan Zou

  • Prediction of human protein subcellular localization using deep learning

    Leyi Wei;Leyi Wei;Yijie Ding;Ran Su;Ran Su;Jijun Tang

  • Identification of drug-side effect association via multiple information integration with centered kernel alignment

    Yijie Ding;Yijie Ding;Jijun Tang;Jijun Tang;Fei Guo

  • Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus

    Yan Zhang;Lin An;Jie Xu;Bo Zhang

  • Identification of drug-target interactions via multiple information integration

    Yijie Ding;Jijun Tang;Jijun Tang;Fei Guo

  • Steps toward accurate reconstructions of phylogenies from gene-order data

    Bernard M. E. Moret;Jijun Tang;Li-San Wang;Tandy Warnow

  • Pretata: predicting TATA binding proteins with novel features and dimensionality reduction strategy

    Quan Zou;Shixiang Wan;Shixiang Wan;Ying Ju;Jijun Tang;Jijun Tang

  • A computational approach for examining the roots and spreading patterns of fake news: Evolution tree analysis

    S. Mo Jang;Tieming Geng;Jo-Yun Queenie Li;Ruofan Xia

  • Predicting protein-protein interactions via multivariate mutual information of protein sequences

    Yijie Ding;Jijun Tang;Jijun Tang;Fei Guo

  • Identification of protein subcellular localization via integrating evolutionary and physicochemical information into Chou’s general PseAAC

    Yinan Shen;Jijun Tang;Jijun Tang;Fei Guo

  • Identification of Drug–Target Interactions via Dual Laplacian Regularized Least Squares with Multiple Kernel Fusion

    Yijie Ding;Jijun Tang;Jijun Tang;Fei Guo

  • SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides

    Leyi Wei;Leyi Wei;Jijun Tang;Quan Zou

  • MLGO: phylogeny reconstruction and ancestral inference from gene-order data.

    Fei Hu;Fei Hu;Yu Lin;Jijun Tang;Jijun Tang

  • PhosPred-RF: A Novel Sequence-Based Predictor for Phosphorylation Sites Using Sequential Information Only

    Leyi Wei;Pengwei Xing;Jijun Tang;Quan Zou

  • A comprehensive overview and critical evaluation of gene regulatory network inference technologies

    Mengyuan Zhao;Wenying He;Jijun Tang;Quan Zou

  • Inversion Medians Outperform Breakpoint Medians in Phylogeny Reconstruction from Gene-Order Data

    Bernard M. E. Moret;Adam C. Siepel;Jijun Tang;Tao Liu

  • Scaling up accurate phylogenetic reconstruction from gene-order data

    Jijun Tang;Bernard M. E. Moret

  • DeepAVP: A Dual-Channel Deep Neural Network for Identifying Variable-Length Antiviral Peptides

    Jiawei Li;Yuqian Pu;Jijun Tang;Quan Zou

  • Identification of membrane protein types via multivariate information fusion with Hilbert–Schmidt Independence Criterion

    Hao Wang;Yijie Ding;Jijun Tang;Jijun Tang;Fei Guo

  • MK-FSVM-SVDD: A Multiple Kernel-based Fuzzy SVM Model for Predicting DNA-binding Proteins via Support Vector Data Description

    Yi Zou;Hongjie Wu;Xiaoyi Guo;Li Peng

  • Identification of Protein–Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information

    Yijie Ding;Jijun Tang;Jijun Tang;Fei Guo

  • Identification of drug–target interactions via fuzzy bipartite local model

    Yijie Ding;Jijun Tang;Jijun Tang;Fei Guo

  • Reconstructing phylogenies from gene-content and gene-order data

    Bernard M. E. Moret;Jijun Tang;Tandy J. Warnow

Frequent Co-Authors

Bernard M. E. Moret
Bernard M. E. Moret École Polytechnique Fédérale de Lausanne
Quan Zou
Quan Zou University of Electronic Science and Technology of China
Leyi Wei
Leyi Wei Shandong University
Roger A. Dougal
Roger A. Dougal University of South Carolina
Claude W. dePamphilis
Claude W. dePamphilis Pennsylvania State University
David A. Bader
David A. Bader New Jersey Institute of Technology
David C. Samuels
David C. Samuels Vanderbilt University
Hao Wang
Hao Wang Tianjin University
Li-San Wang
Li-San Wang University of Pennsylvania
Austin L. Hughes
Austin L. Hughes University of South Carolina

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