Fang Ge

681 total citations
38 papers, 474 citations indexed

About

Fang Ge is a scholar working on Molecular Biology, Computational Theory and Mathematics and Genetics. According to data from OpenAlex, Fang Ge has authored 38 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 5 papers in Genetics. Recurrent topics in Fang Ge's work include Machine Learning in Bioinformatics (24 papers), RNA and protein synthesis mechanisms (16 papers) and vaccines and immunoinformatics approaches (8 papers). Fang Ge is often cited by papers focused on Machine Learning in Bioinformatics (24 papers), RNA and protein synthesis mechanisms (16 papers) and vaccines and immunoinformatics approaches (8 papers). Fang Ge collaborates with scholars based in China, Australia and Thailand. Fang Ge's co-authors include Dong‐Jun Yu, Muhammad Arif, Jiangning Song, Fuyi Li, Muhammad Kabir, Saeed Ahmed, Yiheng Zhu, Min Li, Farman Ali and Saeed Ahmad and has published in prestigious journals such as International Journal of Molecular Sciences, BMC Bioinformatics and Journal of Chemical Information and Modeling.

In The Last Decade

Fang Ge

33 papers receiving 470 citations

Peers

Fang Ge
Yixiao Zhai China
Wenjia He China
Subu Subramanian United States
Runyu Jing China
Zimei Zhang China
Lufeng Yuan China
Ya-Wei Zhao China
Muhammad Arif China
Gaurav Mishra India
Yixiao Zhai China
Fang Ge
Citations per year, relative to Fang Ge Fang Ge (= 1×) peers Yixiao Zhai

Countries citing papers authored by Fang Ge

Since Specialization
Citations

This map shows the geographic impact of Fang Ge'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 Fang Ge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fang Ge more than expected).

Fields of papers citing papers by Fang Ge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fang Ge. 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 Fang Ge. The network helps show where Fang Ge may publish in the future.

Co-authorship network of co-authors of Fang Ge

This figure shows the co-authorship network connecting the top 25 collaborators of Fang Ge. A scholar is included among the top collaborators of Fang Ge 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 Fang Ge. Fang Ge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Wu, Jia‐shun, et al.. (2025). Identification of Protein-Nucleotide Binding Residues With Deep Multi-Task and Multi-Scale Learning. IEEE Journal of Biomedical and Health Informatics. 29(7). 5329–5338.
3.
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Ge, Fang, et al.. (2024). FCMSTrans: Accurate Prediction of Disease-Associated nsSNPs by Utilizing Multiscale Convolution and Deep Feature Combination within a Transformer Framework. Journal of Chemical Information and Modeling. 64(4). 1394–1406. 12 indexed citations
5.
Yang, Xibei, et al.. (2024). GPTrans: A Biological Language Model-Based Approach for Predicting Disease-Associated Mutations in G Protein-Coupled Receptors. Journal of Chemical Information and Modeling. 64(24). 9626–9642. 2 indexed citations
6.
Zhang, Ming, et al.. (2024). MetalTrans: A Biological Language Model-Based Approach for Predicting Disease-Associated Mutations in Protein Metal-Binding Sites. Journal of Chemical Information and Modeling. 64(15). 6216–6229. 4 indexed citations
7.
Ge, Fang, et al.. (2024). PRITrans: A Transformer-Based Approach for the Prediction of the Effects of Missense Mutation on Protein–RNA Interactions. International Journal of Molecular Sciences. 25(22). 12348–12348. 1 indexed citations
8.
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Arif, Muhammad, et al.. (2024). DPI_CDF: druggable protein identifier using cascade deep forest. BMC Bioinformatics. 25(1). 145–145. 17 indexed citations
10.
Wu, Jia‐shun, Yan Liu, Fang Ge, & Dong‐Jun Yu. (2024). Prediction of protein-ATP binding residues using multi-view feature learning via contextual-based co-attention network. Computers in Biology and Medicine. 172. 108227–108227. 11 indexed citations
11.
Wang, Zhikang, Xuan Yu, Xiaoyu Wang, et al.. (2024). MORE: a multi-omics data-driven hypergraph integration network for biomedical data classification and biomarker identification. Briefings in Bioinformatics. 26(1). 6 indexed citations
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Zhou, Jianling, et al.. (2024). DeepBP: Ensemble deep learning strategy for bioactive peptide prediction. BMC Bioinformatics. 25(1). 352–352. 7 indexed citations
14.
Ge, Fang, Yan Liu, Yumeng Zhang, et al.. (2024). TransEFVP: A Two-Stage Approach for the Prediction of Human Pathogenic Variants Based on Protein Sequence Embedding Fusion. Journal of Chemical Information and Modeling. 64(4). 1407–1418. 14 indexed citations
15.
Zhang, Ying, Fang Ge, Fuyi Li, et al.. (2023). Prediction of Multiple Types of RNA Modifications via Biological Language Model. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(5). 3205–3214. 14 indexed citations
16.
Ge, Fang, Chen Li, Shahid Iqbal, et al.. (2022). VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants. Briefings in Bioinformatics. 24(1). 18 indexed citations
17.
Zhao, Jian, Chen Li, Fang Ge, et al.. (2022). csORF-finder: an effective ensemble learning framework for accurate identification of multi-species coding short open reading frames. Briefings in Bioinformatics. 23(6). 16 indexed citations
18.
Cheng, Nuo, Ling Zhou, Dan Liu, et al.. (2021). Human umbilical cord mesenchymal stromal cells promote the regeneration of severe endometrial damage in a rat model. Acta Biochimica et Biophysica Sinica. 54(1). 148–151. 7 indexed citations
19.
Ge, Fang, Yiheng Zhu, Jian Xu, et al.. (2021). MutTMPredictor: Robust and accurate cascade XGBoost classifier for prediction of mutations in transmembrane proteins. Computational and Structural Biotechnology Journal. 19. 6400–6416. 23 indexed citations
20.
Ge, Fang, Muhammad Arif, & Dong‐Jun Yu. (2021). DeepnsSNPs: Accurate prediction of non-synonymous single-nucleotide polymorphisms by combining multi-scale convolutional neural network and residue environment information. Chemometrics and Intelligent Laboratory Systems. 215. 104326–104326. 17 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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