JunJie Wee

462 total citations
22 papers, 309 citations indexed

About

JunJie Wee is a scholar working on Molecular Biology, Computational Theory and Mathematics and Biophysics. According to data from OpenAlex, JunJie Wee has authored 22 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 3 papers in Biophysics. Recurrent topics in JunJie Wee's work include Computational Drug Discovery Methods (11 papers), Protein Structure and Dynamics (8 papers) and Bioinformatics and Genomic Networks (7 papers). JunJie Wee is often cited by papers focused on Computational Drug Discovery Methods (11 papers), Protein Structure and Dynamics (8 papers) and Bioinformatics and Genomic Networks (7 papers). JunJie Wee collaborates with scholars based in Singapore, United States and China. JunJie Wee's co-authors include Kelin Xia, Guo‐Wei Wei, Tze Chien Sum, Qiang Xu, D. Vijay Anand, Ginestra Bianconi, Jiahui Chen, Guo‐Wei Wei, Cong Shen and Xiang Liu and has published in prestigious journals such as Scientific Reports, Advanced Science and Journal of Chemical Information and Modeling.

In The Last Decade

JunJie Wee

21 papers receiving 305 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
JunJie Wee Singapore	9	178	163	82	22	22	22	309
Yuchi Qiu United States	12	134 0.8×	264 1.6×	19 0.2×	23 1.0×	4 0.2×	20	429
Odin Zhang China	11	191 1.1×	203 1.2×	87 1.1×	19 0.9×	8 0.4×	27	328
Tomasz Danel Poland	8	191 1.1×	142 0.9×	139 1.7×	32 1.5×	5 0.2×	16	304
Jake P. Taylor‐King United Kingdom	8	80 0.4×	148 0.9×	49 0.6×	52 2.4×	2 0.1×	14	283
Maryam Bagherian United States	5	271 1.5×	237 1.5×	81 1.0×	37 1.7×	7 0.3×	14	344
Oleksii Prykhodko Sweden	2	388 2.2×	277 1.7×	315 3.8×	29 1.3×	15 0.7×	2	482
Sabrina Jaeger-Honz Germany	6	380 2.1×	299 1.8×	252 3.1×	32 1.5×	20 0.9×	10	553
Clemens Isert Switzerland	8	242 1.4×	186 1.1×	188 2.3×	17 0.8×	10 0.5×	12	336
Derek van Tilborg Netherlands	6	158 0.9×	145 0.9×	115 1.4×	16 0.7×	4 0.2×	7	288
Alexander L. Button Switzerland	6	131 0.7×	140 0.9×	89 1.1×	15 0.7×	5 0.2×	7	250

Countries citing papers authored by JunJie Wee

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of JunJie Wee

This figure shows the co-authorship network connecting the top 25 collaborators of JunJie Wee. A scholar is included among the top collaborators of JunJie Wee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with JunJie Wee. JunJie Wee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Hozumi, Yuta, et al.. (2025). CAP: Commutative algebra prediction of protein-nucleic acid binding affinities. Machine Learning Science and Technology. 6(4). 45068–45068.

Wee, JunJie & Guo-Wei Wei. (2025). Rapid response to fast viral evolution using AlphaFold 3-assisted topological deep learning. Virus Evolution. 11(1). veaf026–veaf026. 2 indexed citations

Wee, JunJie & Jian Jiang. (2025). A Review of Topological Data Analysis and Topological Deep Learning in Molecular Sciences. Journal of Chemical Information and Modeling. 65(23). 12691–12706. 1 indexed citations

Feng, Hongsong, et al.. (2025). CAML: Commutative Algebra Machine Learning─A Case Study on Protein–Ligand Binding Affinity Prediction. Journal of Chemical Information and Modeling. 65(13). 6732–6743. 3 indexed citations

Chen, Dong, Hongyan Du, JunJie Wee, et al.. (2025). Drug Resistance Predictions Based on a Directed Flag Transformer. Advanced Science. 12(36). e02756–e02756. 3 indexed citations

Wee, JunJie, Jiahui Chen, & Guo‐Wei Wei. (2024). Preventing future zoonosis: SARS-CoV-2 mutations enhance human–animal cross-transmission. Computers in Biology and Medicine. 182. 109101–109101. 6 indexed citations

Shen, Cong, et al.. (2024). Curvature-enhanced graph convolutional network for biomolecular interaction prediction. Computational and Structural Biotechnology Journal. 23. 1016–1025. 8 indexed citations

Wee, JunJie, Jiahui Chen, Kelin Xia, & Guo‐Wei Wei. (2024). Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation. Computers in Biology and Medicine. 169. 107918–107918. 10 indexed citations

Wee, JunJie & Guo‐Wei Wei. (2024). Evaluation of AlphaFold 3’s Protein–Protein Complexes for Predicting Binding Free Energy Changes upon Mutation. Journal of Chemical Information and Modeling. 64(16). 6676–6683. 37 indexed citations

10.

Xia, Kelin, Xiang Liu, & JunJie Wee. (2023). Persistent Homology for RNA Data Analysis. Methods in molecular biology. 2627. 211–229. 4 indexed citations

11.

Wee, JunJie, Ginestra Bianconi, & Kelin Xia. (2023). Persistent Dirac for molecular representation. Scientific Reports. 13(1). 11183–11183. 25 indexed citations

12.

Wee, JunJie, et al.. (2023). Multiscale Topological Indices for the Quantitative Prediction of SARS CoV-2 Binding Affinity Change upon Mutations. Journal of Chemical Information and Modeling. 63(13). 4216–4227. 5 indexed citations

13.

Wee, JunJie, et al.. (2023). Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery. Journal of Chemical Information and Modeling. 63(10). 2928–2935. 15 indexed citations

14.

Wee, JunJie, et al.. (2022). Hodge theory-based biomolecular data analysis. Scientific Reports. 12(1). 9699–9699. 8 indexed citations

15.

Anand, D. Vijay, Qiang Xu, JunJie Wee, Kelin Xia, & Tze Chien Sum. (2022). Topological feature engineering for machine learning based halide perovskite materials design. npj Computational Materials. 8(1). 48 indexed citations

16.

Gong, Weikang, et al.. (2022). Persistent spectral simplicial complex-based machine learning for chromosomal structural analysis in cellular differentiation. Briefings in Bioinformatics. 23(4). 7 indexed citations

17.

Wee, JunJie & Kelin Xia. (2021). Forman persistent Ricci curvature (FPRC)-based machine learning models for protein–ligand binding affinity prediction. Briefings in Bioinformatics. 22(6). 45 indexed citations

18.

Wee, JunJie & Kelin Xia. (2021). Ollivier Persistent Ricci Curvature-Based Machine Learning for the Protein–Ligand Binding Affinity Prediction. Journal of Chemical Information and Modeling. 61(4). 1617–1626. 42 indexed citations

19.

Wee, JunJie, et al.. (2019). Korenblum constants for some function spaces. Proceedings of the American Mathematical Society. 148(3). 1175–1185. 2 indexed citations

20.

Cho, Hyunwoo, et al.. (2003). cDNA Microarray Data Based Classification of Cancers Using Neural Networks and Genetic Algorithms. TechConnect Briefs. 1(2003). 28–31. 4 indexed citations

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.

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