JunJie Wee
Impact in
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- Computational Drug Discovery Methods
- Topological and Geometric Data Analysis
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- Cell Image Analysis Techniques
Papers in
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- Protein Structure and Dynamics 8
- Bioinformatics and Genomic Networks 7
- Genomics and Chromatin Dynamics 3
- Machine Learning in Bioinformatics 2
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- Computational Drug Discovery Methods 11
- Topological and Geometric Data Analysis 5
- Co-authors
- Kelin Xia (13 shared papers)Guo‐Wei Wei (3 shared papers)Qiang Xu (1 shared paper)D. Vijay Anand (1 shared paper)Tze Chien Sum (1 shared paper)Ginestra Bianconi (1 shared paper)Jiahui Chen (3 shared papers)Cong Shen (2 shared papers)
- Journals
- Journal of Chemical Information and Modeling (7 papers)Briefings in Bioinformatics (3 papers)Computers in Biology and Medicine (2 papers)Scientific Reports (2 papers)npj Computational Materials (1 paper)
- Partner nations
- SingaporeUnited StatesChina
In The Last Decade
JunJie Wee
21 papers receiving 305 citations
Peers
Comparison fields: 5 of 77
- Computational Theory and Mathematics 178
- Biophysics 19
- Molecular Biology 163
- Mathematical Physics 16
- Materials Chemistry 82
Countries citing papers authored by JunJie Wee
This map shows the geographic impact of JunJie Wee'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 JunJie Wee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites JunJie Wee more than expected).
Fields of papers citing papers by JunJie Wee
This network shows the impact of papers produced by JunJie Wee. 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 JunJie Wee. The network helps show where JunJie Wee may publish in the future.
Co-authors
The 25 scholars most cited alongside JunJie Wee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 48 | |
| 2 | 2021 | 45 | |
| 3 | 2021 | 42 | |
| 4 | 2024 | 37 | |
| 5 | 2022 | 32 | |
| 6 | 2023 | 25 | |
| 7 | 2023 | 15 | |
| 8 | 2024 | 10 | |
| 9 | 2024 | 8 | |
| 10 | 2022 | 8 | |
| 11 | 2022 | 7 | |
| 12 | 2024 | 6 | |
| 13 | 2023 | 5 | |
| 14 | 2023 | 4 | |
| 15 | cDNA Microarray Data Based Classification of Cancers Using Neural Networks and Genetic Algorithms | 2003 | 4 |
| 16 | 2025 | 3 | |
| 17 | 2025 | 3 | |
| 18 | 2025 | 2 | |
| 19 | 2019 | 2 | |
| 20 | 2025 | 2 |
About JunJie Wee
JunJie Wee is a scholar working on Molecular Biology, Computational Theory and Mathematics, Biophysics, Materials Chemistry and Mathematical Physics, having authored 22 papers that have together received 309 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Protein Structure and Dynamics (8 papers), Bioinformatics and Genomic Networks (7 papers), Topological and Geometric Data Analysis (5 papers), Cell Image Analysis Techniques (3 papers), Genomics and Chromatin Dynamics (3 papers), Machine Learning in Bioinformatics (2 papers) and Machine Learning in Materials Science (2 papers). The work is most often cited by research in Computational Theory and Mathematics (178 citations), Biophysics (19 citations), Molecular Biology (163 citations), Mathematical Physics (16 citations) and Materials Chemistry (82 citations). JunJie Wee has collaborated with scholars based in Singapore, United States and China. Frequent co-authors include Kelin Xia, Guo‐Wei Wei, Qiang Xu, D. Vijay Anand, Tze Chien Sum, Ginestra Bianconi, Jiahui Chen, Cong Shen, Guo‐Wei Wei and Xiang Liu. Their work appears in journals such as Journal of Chemical Information and Modeling, Briefings in Bioinformatics, Computers in Biology and Medicine, Scientific Reports and npj Computational Materials.
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.