Ming Wen

Active 2001–2026

264
Papers
18,675
Citations
62
h-index
183
i10-index

Citations

Citations per year for Ming Wen1920: 1 citations1995: 1 citations1996: 1 citations1999: 1 citations2000: 1 citations2003: 3 citations2004: 5 citations2005: 17 citations2006: 18 citations2007: 26 citations2008: 24 citations2009: 37 citations2010: 75 citations2011: 115 citations2012: 106 citations2013: 90 citations2014: 102 citations2015: 92 citations2016: 83 citations2017: 134 citations2018: 226 citations2019: 557 citations2020: 637 citations2021: 795 citations2022: 684 citations2023: 716 citations2024: 1,151 citations2025: 856 citations2026: 252 citations2027: 2 citations1921–1994: no citations, so these years are not shown1997–1998: no citations, so these years are not shown2001–2002: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 2,762 citing papers, 29.4% of this breakdownUnited States: 1,696 citing papers, 18% of this breakdownUnited Kingdom: 446 citing papers, 4.7% of this breakdownCanada: 360 citing papers, 3.8% of this breakdownGermany: 306 citing papers, 3.3% of this breakdownAustralia: 293 citing papers, 3.1% of this breakdownFrance: 248 citing papers, 2.6% of this breakdownSingapore: 223 citing papers, 2.4% of this breakdownHong Kong: 214 citing papers, 2.3% of this breakdownIndia: 192 citing papers, 2% of this breakdownSouth Korea: 183 citing papers, 2% of this breakdownJapan: 171 citing papers, 1.8% of this breakdown
0%29.4%Other 24.6%

Fields

  • Computer Science35.2%
  • Biochemistry, Genetics and Molecular Biology20.6%
  • Medicine12.3%
  • Agricultural and Biological Sciences6.5%
  • Immunology and Microbiology5.1%
  • Social Sciences4.6%
  • Other15.7%

Topics

  • Software Engineering Research5.3%
  • Software Testing and Debugging Techniques4%
  • Computational Drug Discovery Methods2.9%
  • Software Reliability and Analysis Research2.6%
  • Genomics and Phylogenetic Studies2.1%
  • Software System Performance and Reliability2%
  • Other81.1%

Coauthors

All papers

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  1. Regulating active hydrogen adsorbed on grain boundary defects of nano-nickel for boosting ammonia electrosynthesis from nitrate

    Authors: , , , , , , , - Energy & Environmental Science 2023 cited by 359

  2. Deep-Learning-Based Drug–Target Interaction Prediction

    Authors: , , , , , , - Journal of Proteome Research 2017 cited by 601

  3. Context-aware patch generation for better automated program repair

    Authors: , , , , - Conference on Software Engineering, ICSE 2018 cited by 332

  4. DCT-GAN: Dilated Convolutional Transformer-Based GAN for Time Series Anomaly Detection

    Authors: , , , , - IEEE Transactions on Knowledge and Data Engineering, IEEE Trans. Knowl. Data Eng. 2021 cited by 147

  5. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

    Authors: , , , , , , , , - Journal of Computer-Aided Molecular Design, J. Comput. Aided Mol. Des. 2016 cited by 495

  6. What's Wrong with Your Code Generated by Large Language Models? An Extensive Study

    Authors: , , , , , , , , , , , , , , , , , , , , , , , - arXiv (Cornell University), CoRR 2024 cited by 63

  7. Mapping the human DC lineage through the integration of high-dimensional techniques

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Muzlifah Haniffa, Philippe Benaroch, Andreas Schlitzer, Joachim L. Schultze, Evan W. Newell, Florent Ginhoux - Science 2017 cited by 571

  8. A study on Prompt Design, Advantages and Limitations of ChatGPT for Deep Learning Program Repair

    Authors: , , , - Automated Software Engineering, Autom. Softw. Eng. 2025 cited by 70

  9. Empowering Practical Root Cause Analysis by Large Language Models for Cloud Incidents

    Authors: , , , , , , , , , , , , , , , , , - Nineteenth European Conference on Computer Systems, EuroSys 2024 cited by 114

  10. Historical Spectrum Based Fault Localization

    Authors: , , , , , , - IEEE Transactions on Software Engineering, IEEE Trans. Software Eng. 2019 cited by 87

  11. ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting

    Authors: , , , , , , , , - Journal of Chemical Information and Modeling, J. Chem. Inf. Model. 2016 cited by 251

  12. DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs

    Authors: , , , , , , - Conference on Software Engineering, ICSE 2022 cited by 50

  13. The genome of the cucumber, Cucumis sativus L.

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Quanfei Huang, Bo Li, Zhaoling Xuan, Jianjun Cao, Asan, Zhigang Wu, Juanbin Zhang, Qingle Cai, Yinqi Bai, Bowen Zhao, Yonghua Han, Ying Li, Xuefeng Li, Shenhao Wang, Qiuxiang Shi, Shiqiang Liu, Won Kyong Cho, Jae‐Yean Kim, Yong Xu, Katarzyna Heller-Uszyńska, H. Miao, Zhouchao Cheng, Shengping Zhang, Jian Wu, Yuhong Yang, Houxiang Kang, Man Li, Huiqing Liang, Xiaoli Ren, Zhongbin Shi, Ming Wen, Min Jian, Hailong Yang, Guojie Zhang, Zhentao Yang, Rui Chen, Shifang Liu, Jianwen Li, Lijia Ma, Hui Liu, Yan Zhou, Jing Zhao, Xiaodong Fang, Guoqing Li, Lin Fang, Yingrui Li, Dongyuan Liu, Hongkun Zheng, Yong Zhang, Nan Qin, Zhuo Li, Guohua Yang, Shuang Yang, Lars Bolund, Karsten Kristiansen, Hancheng Zheng, Shaochuan Li, Xiuqing Zhang, Huanming Yang, Jian Wang, Rifei Sun, Baoxi Zhang, Shuzhi Jiang, Jun Wang, Yongchen Du, Songgang Li - Nature Genetics 2009 cited by 1,503

  14. Dampened NLRP3-mediated inflammation in bats and implications for a special viral reservoir host

    Authors: , , , , , , , , , , , , , , , , , , - Nature Microbiology 2019 cited by 353

  15. Kling-Foley: Multimodal Diffusion Transformer for High-Quality Video-to-Audio Generation

    Authors: , , , , , , , , , , , , , , , , , , , , , , - ArXiv.org, CoRR 2025 cited by 34

  16. Context-Aware Code Change Embedding for Better Patch Correctness Assessment

    Authors: , , , - ACM Transactions on Software Engineering and Methodology, ACM Trans. Softw. Eng. Methodol. 2022 cited by 60

  17. Automated Patch Correctness Assessment: How Far are We?

    Authors: , , , , , , , - IEEE/ACM International Conference on Automated Software Engineering, ASE 2020 cited by 78

  18. Watchman: monitoring dependency conflicts for Python library ecosystem

    Authors: , , , , , , , , , - ACM/IEEE 42nd International Conference on Software Engineering, ICSE 2020 cited by 65

  19. CT-based radiomics analysis of different machine learning models for differentiating benign and malignant parotid tumors

    Authors: , , , - European Radiology 2022 cited by 99

  20. Locus: locating bugs from software changes

    Authors: , , - IEEE/ACM International Conference on Automated Software Engineering, ASE 2016 cited by 174

  21. Exploring and exploiting the correlations between bug-inducing and bug-fixing commits

    Authors: , , , , , , - ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/SIGSOFT FSE 2019 cited by 57

  22. Generalization-Enhanced Code Vulnerability Detection via Multi-Task Instruction Fine-Tuning

    Authors: , , , , , , , - Findings of the Association for Computational Linguistics ACL 2024, ACL (Findings) 2024 cited by 27

  23. Do the dependency conflicts in my project matter?

    Authors: , , , , , , , , - ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/SIGSOFT FSE 2018 cited by 81

  24. Aroc: An Automatic Repair Framework for On-Chain Smart Contracts

    Authors: , , , , , - IEEE Transactions on Software Engineering, IEEE Trans. Software Eng. 2021 cited by 40