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BMC Bioinformatics
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June 25, 2024
iProL: identifying DNA promoters from sequence information based on Longformer pre-trained model
Binchao Peng, Guicong Sun, Yongxian Fan
Plos One
|
September 21, 2023
An interpretable machine learning framework for diagnosis and prognosis of COVID-19
Yongxian Fan, Meng Liu, Guicong Sun
Computational Biology and Chemistry
|
May 11, 2025
iEnhancer-DS: Attention-based improved densenet for identifying enhancers and their strength
Yongxian Fan, Chen Wang, Guicong Sun
Computational Biology and Chemistry
|
November 28, 2025
DeepHFFT-m7G: A dual-channel self-attention and hybrid feature fusion framework for RNA m7G modification identification
Yongxian Fan, Zeheng Wu, Guicong Sun
BMC Bioinformatics
|
September 6, 2023
IHCP: interpretable hepatitis C prediction system based on black-box machine learning models
Yongxian Fan, Xiqian Lu, Guicong Sun
BMC Bioinformatics
|
June 22, 2023
DeepASDPred: a CNN-LSTM-based deep learning method for Autism spectrum disorders risk RNA identification
Yongxian Fan, Hui Xiong, Guicong Sun
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|
May 10, 2022
ELMo4m6A: A Contextual Language Embedding-Based Predictor for Detecting RNA N6-Methyladenosine Sites
Yongxian Fan, Guicong Sun, Xiaoyong Pan
IEEE Transactions on Computational Biology and Bioinformatics
|
November 19, 2025
iDRKAN: Interpretable miRNA-Disease Association Prediction Based on Dual-Graph Representation Learning and Kolmogorov-Arnold Network
Yangfeng Zhu, Yongxian Fan, Guicong Sun
Interdisciplinary Sciences, Computational Life Sciences
|
February 17, 2025
MVGNCDA: Identifying Potential circRNA-Disease Associations Based on Multi-view Graph Convolutional Networks and Network Embeddings
Guicong Sun, Mengxin Zheng, Yongxian Fan, et al.
IEEE Transactions on Computational Biology and Bioinformatics
|
May 21, 2026
FGAIM: Identifying Drug-Target Activation and Inhibition Mechanisms via Inductive Graph Neural Networks Based on Fine-Grained Interaction Strategies
Yi Tang, Yongxian Fan, Guicong Sun, et al.
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Search research articles
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Showing results (1-10 of 13) with videos related to
Sort By:
Page
of 2
BMC Bioinformatics
|
June 25, 2024
iProL: identifying DNA promoters from sequence information based on Longformer pre-trained model
Binchao Peng, Guicong Sun, Yongxian Fan
Plos One
|
September 21, 2023
An interpretable machine learning framework for diagnosis and prognosis of COVID-19
Yongxian Fan, Meng Liu, Guicong Sun
Computational Biology and Chemistry
|
May 11, 2025
iEnhancer-DS: Attention-based improved densenet for identifying enhancers and their strength
Yongxian Fan, Chen Wang, Guicong Sun
Computational Biology and Chemistry
|
November 28, 2025
DeepHFFT-m7G: A dual-channel self-attention and hybrid feature fusion framework for RNA m7G modification identification
Yongxian Fan, Zeheng Wu, Guicong Sun
BMC Bioinformatics
|
September 6, 2023
IHCP: interpretable hepatitis C prediction system based on black-box machine learning models
Yongxian Fan, Xiqian Lu, Guicong Sun
BMC Bioinformatics
|
June 22, 2023
DeepASDPred: a CNN-LSTM-based deep learning method for Autism spectrum disorders risk RNA identification
Yongxian Fan, Hui Xiong, Guicong Sun
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|
May 10, 2022
ELMo4m6A: A Contextual Language Embedding-Based Predictor for Detecting RNA N6-Methyladenosine Sites
Yongxian Fan, Guicong Sun, Xiaoyong Pan
IEEE Transactions on Computational Biology and Bioinformatics
|
November 19, 2025
iDRKAN: Interpretable miRNA-Disease Association Prediction Based on Dual-Graph Representation Learning and Kolmogorov-Arnold Network
Yangfeng Zhu, Yongxian Fan, Guicong Sun
Interdisciplinary Sciences, Computational Life Sciences
|
February 17, 2025
MVGNCDA: Identifying Potential circRNA-Disease Associations Based on Multi-view Graph Convolutional Networks and Network Embeddings
Guicong Sun, Mengxin Zheng, Yongxian Fan, et al.
IEEE Transactions on Computational Biology and Bioinformatics
|
May 21, 2026
FGAIM: Identifying Drug-Target Activation and Inhibition Mechanisms via Inductive Graph Neural Networks Based on Fine-Grained Interaction Strategies
Yi Tang, Yongxian Fan, Guicong Sun, et al.
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of 2