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Dong-Jun Yu

D-Index & Metrics

Computer Science

D-Index
41
Citations
5604
World Ranking
8961
National Ranking
1154

Dong-Jun Yu publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Dong-Jun Yu sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 113 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Dong-Jun Yu D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Dong-Jun Yu sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Dong-Jun Yu is affiliated with Nanjing University of Science and Technology in China, specializing in research at the intersection of biochemistry, genetics, and molecular biology. Their scholarly output spans over 227 publications in this broad field, with a focus on molecular biology and computational applications in life sciences.

Their work is grounded strongly in the subfields of molecular biology, computational theory and mathematics, artificial intelligence, biophysics, and materials chemistry. This range reflects a multidisciplinary approach that integrates biological sciences with computational and chemical insights.

Prominent topics covered in their research include:

  • Machine Learning in Bioinformatics
  • RNA and protein synthesis mechanisms
  • Protein Structure and Dynamics
  • Computational Drug Discovery Methods
  • Genomics and Phylogenetic Studies
  • Vaccines and immunoinformatics approaches
  • Bioinformatics and Genomic Networks

Their publications appear frequently in several scientific journals, with notable contributions to the following venues:

  • Journal of Chemical Information and Modeling
  • Briefings in Bioinformatics
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Bioinformatics
  • IEEE/ACM Transactions on Computational Biology and Bioinformatics

Some of the recent papers authored include:

  • "Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides," 2021, Briefings in Bioinformatics
  • "Deducing high-accuracy protein contact-maps from a triplet of coevolutionary matrices through deep residual convolutional networks," 2021, PLoS Computational Biology
  • "TargetCPP: accurate prediction of cell-penetrating peptides from optimized multi-scale features using gradient boost decision tree," 2020, Journal of Computer-Aided Molecular Design
  • "Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites," 2021, Briefings in Bioinformatics
  • "StackACPred: Prediction of anticancer peptides by integrating optimized multiple feature descriptors with stacked ensemble approach," 2021, Chemometrics and Intelligent Laboratory Systems

The scientist collaborates regularly with a group of frequent co-authors, reflecting sustained research partnerships. These co-authors include Jiangning Song, Fang Ge, Yan Liu, Yiheng Zhu, and Long-Chen Shen.

Best Publications

  • Combination of interval-valued fuzzy set and soft set

    Xibei Yang;Tsau Young Lin;Jingyu Yang;Yan Li

  • Dominance-based rough set approach and knowledge reductions in incomplete ordered information system

    Xibei Yang;Jingyu Yang;Chen Wu;Dongjun Yu

  • Dominance-based rough set approach to incomplete interval-valued information system

    Xibei Yang;Dongjun Yu;Jingyu Yang;Lihua Wei

  • Multi-label learning with label-specific feature reduction

    Suping Xu;Xibei Yang;Hualong Yu;Dong-Jun Yu

  • ResPRE: high-accuracy protein contact prediction by coupling precision matrix with deep residual neural networks.

    Yang Li;Yang Li;Jun Hu;Jun Hu;Chengxin Zhang;Dong-Jun Yu

  • Designing Template-Free Predictor for Targeting Protein-Ligand Binding Sites with Classifier Ensemble and Spatial Clustering

    Dong-Jun Yu;Jun Hu;Jing Yang;Hong-Bin Shen

  • Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides.

    Jing Xu;Fuyi Li;André Leier;Dongxu Xiang

  • Protein-protein interaction sites prediction by ensembling SVM and sample-weighted random forests

    Zhi-Sen Wei;Ke Han;Jing-Yu Yang;Hong-Bin Shen

  • Generalization of Soft Set Theory: From Crisp to Fuzzy Case

    Xibei Yang;Dongjun Yu;Jingyu Yang;Chen Wu;Chen Wu

  • Ensembling multiple raw coevolutionary features with deep residual neural networks for contact-map prediction in CASP13.

    Yang Li;Yang Li;Chengxin Zhang;Eric W. Bell;Dong‐Jun Yu;Dong‐Jun Yu

  • An efficient renovation on kernel Fisher discriminant analysis and face recognition experiments

    Yong Xu;Jing-yu Yang;Jianfeng Lu;Dong-jun Yu

  • Predicting Protein-DNA Binding Residues by Weightedly Combining Sequence-Based Features and Boosting Multiple SVMs

    Jun Hu;Yang Li;Ming Zhang;Xibei Yang

  • Least squares twin bounded support vector machines based on L1-norm distance metric for classification

    He Yan;Qiaolin Ye;Qiaolin Ye;Tian’an Zhang;Dong-Jun Yu

  • α-Dominance relation and rough sets in interval-valued information systems

    Xibei Yang;Yong Qi;Dong-Jun Yu;Hualong Yu

  • Deducing high-accuracy protein contact-maps from a triplet of coevolutionary matrices through deep residual convolutional networks.

    Yang Li;Chengxin Zhang;Eric W. Bell;Wei Zheng

  • TargetATPsite: a template-free method for ATP-binding sites prediction with residue evolution image sparse representation and classifier ensemble.

    Dong-Jun Yu;Jun Hu;Yan Huang;Hong-Bin Shen;Hong-Bin Shen

  • Improving protein-ATP binding residues prediction by boosting SVMs with random under-sampling

    Dong-Jun Yu;Jun Hu;Zhen-Min Tang;Hong-Bin Shen

  • LS-align: an atom-level, flexible ligand structural alignment algorithm for high-throughput virtual screening.

    Jun Hu;Jun Hu;Zi Liu;Dong-Jun Yu;Yang Zhang

  • TargetM6A: Identifying N 6 -Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine

    Guang-Qing Li;Zi Liu;Hong-Bin Shen;Dong-Jun Yu

  • DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines.

    Yi-Heng Zhu;Jun Hu;Xiao-Ning Song;Dong-Jun Yu

  • DBPPred-PDSD: Machine learning approach for prediction of DNA-binding proteins using Discrete Wavelet Transform and optimized integrated features space

    Farman Ali;Muhammad Kabir;Muhammad Arif;Zar Nawab Khan Swati;Zar Nawab Khan Swati

Frequent Co-Authors

Jingyu Yang
Jingyu Yang Nanjing University of Science and Technology
Hong-Bin Shen
Hong-Bin Shen Shanghai Jiao Tong University
Xibei Yang
Xibei Yang Jiangsu University of Science and Technology
Yang Zhang
Yang Zhang University of Michigan–Ann Arbor
Jiangning Song
Jiangning Song Monash University
Xiaojun Wu
Xiaojun Wu University of Science and Technology of China
Jian Yang
Jian Yang University of Birmingham
Edwin R. Hancock
Edwin R. Hancock University of York
William A. P. Smith
William A. P. Smith University of York
Yaser Daanial Khan
Yaser Daanial Khan University of Management and Technology

External Links

Personal website of Dong-Jun Yu

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Best Scientists Citing Dong-Jun Yu

Xibei Yang

Xibei Yang

Jiangsu University of Science and Technology

Publications: 62

Kuo-Chen Chou

Kuo-Chen Chou

The Gordon Life Science Institute

Publications: 44

Yang Zhang

Yang Zhang

University of Michigan–Ann Arbor

Publications: 30

Hamido Fujita

Hamido Fujita

University of Technology Malaysia

Publications: 25

Xuan Xiao

Xuan Xiao

Jingdezhen Ceramic Institute

Publications: 24

Maqsood Hayat

Maqsood Hayat

Abdul Wali Khan University Mardan

Publications: 24

Tianrui Li

Tianrui Li

Southwest Jiaotong University

Publications: 23

Yong Xu

Yong Xu

Harbin Institute of Technology

Publications: 19

Wei Chen

Wei Chen

Chengdu University of Traditional Chinese Medicine

Publications: 17

Hong-Bin Shen

Hong-Bin Shen

Shanghai Jiao Tong University

Publications: 17

Jingyu Yang

Jingyu Yang

Nanjing University of Science and Technology

Publications: 17

Quan Zou

Quan Zou

University of Electronic Science and Technology of China

Publications: 16

Jijun Tang

Jijun Tang

University of South Carolina

Publications: 15

Yuhua Qian

Yuhua Qian

Shanxi University

Publications: 15

Hao Lin

Hao Lin

University of Electronic Science and Technology of China

Publications: 13

Dun Liu

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Publications: 13

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