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Xiangxiang Zeng

Xiangxiang Zeng

D-Index & Metrics

Computer Science

D-Index
56
Citations
10549
World Ranking
4133
National Ranking
554

Overview

Xiangxiang Zeng is affiliated with Hunan University in China and has contributed extensively to research in the intersecting fields of biochemistry, genetics, molecular biology, and computer science. Their work spans various subfields including molecular biology, computational theory and mathematics, materials chemistry, artificial intelligence, and pharmacology.

Their research focuses on several main topics:

  • Computational Drug Discovery Methods
  • Machine Learning in Materials Science
  • Bioinformatics and Genomic Networks
  • Machine Learning in Bioinformatics
  • Protein Structure and Dynamics
  • DNA and Biological Computing
  • Advanced biosensing and bioanalysis techniques

Xiangxiang Zeng has produced a number of recent publications in well-regarded journals. These include:

  • ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties, 2021, Nucleic Acids Research
  • ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support, 2024, Nucleic Acids Research
  • Target identification among known drugs by deep learning from heterogeneous networks, 2020, Chemical Science
  • Repurpose Open Data to Discover Therapeutics for COVID-19 Using Deep Learning, 2020, Journal of Proteome Research
  • Deep generative molecular design reshapes drug discovery, 2022, Cell Reports Medicine

The primary venues where Xiangxiang Zeng publishes include:

  • Briefings in Bioinformatics
  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Bioinformatics
  • Journal of Chemical Information and Modeling

Among frequent collaborators are Bosheng Song, Dongsheng Cao, Yuansheng Liu, Xiangrong Liu, and Quan Zou, each contributing to multiple co-authored works, reflecting ongoing research partnerships.

Best Publications

  • deepDR: a network-based deep learning approach to in silico drug repositioning.

    Xiangxiang Zeng;Siyi Zhu;Xiangrong Liu;Yadi Zhou

  • A comprehensive overview and evaluation of circular RNA detection tools.

    Xiangxiang Zeng;Wei Lin;Maozu Guo;Quan Zou

  • Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks

    Xiangxiang Zeng;Xuan Zhang;Quan Zou

  • Target identification among known drugs by deep learning from heterogeneous networks.

    Xiangxiang Zeng;Siyi Zhu;Weiqiang Lu;Zehui Liu

  • Inferring MicroRNA-Disease Associations by Random Walk on a Heterogeneous Network with Multiple Data Sources

    Yuansheng Liu;Xiangxiang Zeng;Zengyou He;Quan Zou

  • KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction

    Xuan Lin;Zhe Quan;Zhi-Jie Wang;Tengfei Ma

  • Similarity computation strategies in the microRNA-disease network: a survey

    Quan Zou;Jinjin Li;Li Song;Xiangxiang Zeng

  • Repurpose Open Data to Discover Therapeutics for COVID-19 Using Deep Learning.

    Xiangxiang Zeng;Xiang Song;Tengfei Ma;Xiaoqin Pan

  • Prediction of potential disease-associated microRNAs using structural perturbation method.

    Xiangxiang Zeng;Li Liu;Linyuan Lü;Quan Zou

  • Sequence clustering in bioinformatics: an empirical study.

    Quan Zou;Quan Zou;Gang Lin;Xingpeng Jiang;Xiangrong Liu

  • Prediction and Validation of Disease Genes Using HeteSim Scores

    Xiangxiang Zeng;Yuanlu Liao;Yuansheng Liu;Quan Zou

  • Toward better drug discovery with knowledge graph.

    Xiangxiang Zeng;Xinqi Tu;Yuansheng Liu;Xiangzheng Fu

  • Application of deep learning methods in biological networks.

    Shuting Jin;Xiangxiang Zeng;Feng Xia;Wei Huang

  • nDNA-prot: Identification of DNA-binding proteins based on unbalanced classification

    Li Song;Dapeng Li;Xiangxiang Zeng;Yunfeng Wu

  • MUFFIN: multi-scale feature fusion for drug–drug interaction prediction

    Yujie Chen;Tengfei Ma;Xixi Yang;Jianmin Wang

  • Identifying enhancer–promoter interactions with neural network based on pre-trained DNA vectors and attention mechanism

    Zengyan Hong;Xiangxiang Zeng;Leyi Wei;Xiangrong Liu

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

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

  • Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources

    Tseren-Onolt Ishdorj;Alberto Leporati;Linqiang Pan;Xiangxiang Zeng

  • Drug repositioning based on the heterogeneous information fusion graph convolutional network

    Lijun Cai;Changcheng Lu;Junlin Xu;Yajie Meng

  • A novel molecular representation with BiGRU neural networks for learning atom

    Xuan Lin;Zhe Quan;Zhi-Jie Wang;Huang Huang

  • Predicting disease-associated circular RNAs using deep forests combined with positive-unlabeled learning methods.

    Xiangxiang Zeng;Yue Zhong;Wei Lin;Quan Zou

  • Spiking neural p systems with thresholds

    Xiangxiang Zeng;Xingyi Zhang;Tao Song;Linqiang Pan

  • Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning

    Xiangxiang Zeng;Xiang Song;Tengfei Ma;Xiaoqin Pan

Frequent Co-Authors

Quan Zou
Quan Zou University of Electronic Science and Technology of China
Linqiang Pan
Linqiang Pan Huazhong University of Science and Technology
Feixiong Cheng
Feixiong Cheng Case Western Reserve University
Xingyi Zhang
Xingyi Zhang Anhui University
Ruth Nussinov
Ruth Nussinov National Institutes of Health
Stephen C. H. Leung
Stephen C. H. Leung City University of Hong Kong
Linyuan Lü
Linyuan Lü University of Electronic Science and Technology of China
Jijun Tang
Jijun Tang University of South Carolina
Gary G. Yen
Gary G. Yen Oklahoma State University
Bin Luo
Bin Luo Anhui University

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