Mingkun Lu
Impact in
- Health Informatics top 10%
-
- Computational Drug Discovery Methods
Papers in
-
- Machine Learning in Bioinformatics 4
- Metabolomics and Mass Spectrometry Studies 2
- Protein Structure and Dynamics 2
- RNA and protein synthesis mechanisms 2
-
- Computational Drug Discovery Methods 6
- Co-authors
- Feng Zhu (11 shared papers)Minjie Mou (7 shared papers)Fengcheng Li (6 shared papers)Zhaorong Li (6 shared papers)Jiayi Yin (5 shared papers)Yu Chen (3 shared papers)Ziqi Pan (5 shared papers)Haibin Dai (5 shared papers)
- Journals
- Briefings in Bioinformatics (4 papers)Journal of Chemical Information and Modeling (2 papers)Current Drug Metabolism (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)Bioinformatics (1 paper)
- Partner nations
- China
In The Last Decade
Mingkun Lu
15 papers receiving 342 citations
Peers
Comparison fields: 5 of 75
- Health Informatics 14
- Computational Theory and Mathematics 114
- Molecular Biology 224
- Cancer Research 43
- Biophysics 16
Countries citing papers authored by Mingkun Lu
This map shows the geographic impact of Mingkun Lu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mingkun Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingkun Lu more than expected).
Fields of papers citing papers by Mingkun Lu
This network shows the impact of papers produced by Mingkun Lu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mingkun Lu. The network helps show where Mingkun Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingkun Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 74 | |
| 2 | 2023 | 72 | |
| 3 | 2022 | 59 | |
| 4 | 2024 | 38 | |
| 5 | 2022 | 33 | |
| 6 | 2024 | 20 | |
| 7 | 2022 | 12 | |
| 8 | 2023 | 10 | |
| 9 | 2023 | 8 | |
| 10 | 2023 | 8 | |
| 11 | 2024 | 4 | |
| 12 | 2023 | 3 | |
| 13 | 2025 | 2 | |
| 14 | 2020 | 2 | |
| 15 | 2020 | 1 | |
| 16 | 2025 | 0 |
About Mingkun Lu
Mingkun Lu is a scholar working on Molecular Biology, Computational Theory and Mathematics, Spectroscopy, Pharmacology and Cancer Research, having authored 16 papers that have together received 346 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Machine Learning in Bioinformatics (4 papers), MicroRNA in disease regulation (2 papers), Pharmacogenetics and Drug Metabolism (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Protein Structure and Dynamics (2 papers), RNA and protein synthesis mechanisms (2 papers) and Advanced Proteomics Techniques and Applications (2 papers). The work is most often cited by research in Health Informatics (14 citations), Computational Theory and Mathematics (114 citations), Molecular Biology (224 citations), Cancer Research (43 citations) and Biophysics (16 citations). Mingkun Lu has collaborated with scholars based in China. Frequent co-authors include Feng Zhu, Minjie Mou, Fengcheng Li, Zhaorong Li, Jiayi Yin, Yu Chen, Ziqi Pan, Haibin Dai, Lingyan Zheng and Hongning Zhang. Their work appears in journals such as Briefings in Bioinformatics, Journal of Chemical Information and Modeling, Current Drug Metabolism, IEEE Journal of Biomedical and Health Informatics and Bioinformatics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.