Fang Ge

According to our database, Fang Ge authored at least 17 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DeepBP: Ensemble deep learning strategy for bioactive peptide prediction.

Ming Zhang, Jianren Zhou, Xiaohua Wang, Xun Wang, Fang Ge

BMC Bioinform., December, 2024

FCMSTrans: Accurate Prediction of Disease-Associated nsSNPs by Utilizing Multiscale Convolution and Deep Feature Combination within a Transformer Framework.

Ming Zhang, Chao Gong, Fang Ge, Dong-Jun Yu

J. Chem. Inf. Model., February, 2024

TransEFVP: A Two-Stage Approach for the Prediction of Human Pathogenic Variants Based on Protein Sequence Embedding Fusion.

Zihao Yan, Fang Ge, Yan Liu, Yumeng Zhang, Fuyi Li, Jiangning Song, Dong-Jun Yu

J. Chem. Inf. Model., February, 2024

MetalTrans: A Biological Language Model-Based Approach for Predicting Disease-Associated Mutations in Protein Metal-Binding Sites.

Ming Zhang, Xiaohua Wang, Shanruo Xu, Fang Ge, Ian Costa Paixao, Jiangning Song, Dong-Jun Yu

J. Chem. Inf. Model., 2024

GPTrans: A Biological Language Model-Based Approach for Predicting Disease-Associated Mutations in G Protein-Coupled Receptors.

Xiaohua Wang, Ming Zhang, Xibei Yang, Dong-Jun Yu, Fang Ge

J. Chem. Inf. Model., 2024

Prediction of protein-ATP binding residues using multi-view feature learning via contextual-based co-attention network.

Jia-Shun Wu, Yan Liu, Fang Ge, Dong-Jun Yu

Comput. Biol. Medicine, 2024

MLSNet: a deep learning model for predicting transcription factor binding sites.

Yuchuan Zhang, Zhikang Wang, Fang Ge, Xiaoyu Wang, Yiwen Zhang, Shanshan Li, Yuming Guo, Jiangning Song, Dong-Jun Yu

Briefings Bioinform., 2024

MORE: a multi-omics data-driven hypergraph integration network for biomedical data classification and biomarker identification.

Yuhan Wang, Zhikang Wang, Xuan Yu, Xiaoyu Wang, Jiangning Song, Dong-Jun Yu, Fang Ge

Briefings Bioinform., 2024

2023

MMPatho: Leveraging Multilevel Consensus and Evolutionary Information for Enhanced Missense Mutation Pathogenic Prediction.

Fang Ge, Muhammad Arif, Zihao Yan, Hanin H. Alahmadi, Apilak Worachartcheewan, Dong-Jun Yu, Watshara Shoombuatong

J. Chem. Inf. Model., November, 2023

VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants.

Fang Ge, Chen Li, Shahid Iqbal, Muhammad Arif, Fuyi Li, Maha A. Thafar, Zihao Yan, Apilak Worachartcheewan, Xiaofeng Xu, Jiangning Song, Dong-Jun Yu

Briefings Bioinform., January, 2023

Prediction of Multiple Types of RNA Modifications via Biological Language Model.

Ying Zhang, Fang Ge, Fuyi Li, Xibei Yang, Jiangning Song, Dong-Jun Yu

IEEE ACM Trans. Comput. Biol. Bioinform., 2023

2022

csORF-finder: an effective ensemble learning framework for accurate identification of multi-species coding short open reading frames.

Meng Zhang, Jian Zhao, Chen Li, Fang Ge, Jing Wu, Bin Jiang, Jiangning Song, Xiaofeng Song

Briefings Bioinform., November, 2022

DeepCPPred: A Deep Learning Framework for the Discrimination of Cell-Penetrating Peptides and Their Uptake Efficiencies.

Muhammad Arif, Muhammad Kabir, Saeed Ahmed, Abid Khan, Fang Ge, Adel Khelifi, Dong-Jun Yu

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

PROST: AlphaFold2-aware Sequence-Based Predictor to Estimate Protein Stability Changes upon Missense Mutations.

Shahid Iqbal, Fang Ge, Fuyi Li, Tatsuya Akutsu, Yuanting Zheng, Robin B. Gasser, Dong-Jun Yu, Geoffrey I. Webb, Jiangning Song

J. Chem. Inf. Model., 2022

Prediction of disease-associated nsSNPs by integrating multi-scale ResNet models with deep feature fusion.

Fang Ge, Ying Zhang, Jian Xu, Muhammad Arif, Jiangning Song, Dong-Jun Yu

Briefings Bioinform., 2022

2021

Accurate multistage prediction of protein crystallization propensity using deep-cascade forest with sequence-based features.

Yi-Heng Zhu, Jun Hu, Fang Ge, Fuyi Li, Jiangning Song, Yang Zhang, Dong-Jun Yu

Briefings Bioinform., 2021

2020

SSCpred: Single-Sequence-Based Protein Contact Prediction Using Deep Fully Convolutional Network.

Ming-Cai Chen, Yang Li, Yi-Heng Zhu, Fang Ge, Dong-Jun Yu

J. Chem. Inf. Model., 2020