DeepSeq2Drug: An Expandable End-to-end Antiviral Drug Repurposing Framework by Multi-Modal Deep Embeddings
Acknowledgment
We would like to thank all of the anonymous reviewers and editors for their constructive advice.
Citation
Deepseq2drug has been accepted by Computers in Biology and Medicine, and we will update pages when assigned.
Xie W, Yu J, Huang L, et al. DeepSeq2Drug: An Expandable Ensemble End-to-end Anti-viral Drug Repurposing Benchmark Framework by Multi-modal Embeddings and Transfer Learning[J]. Computers in Biology and Medicine, 2024: 108487.
Please cite our paper if you find our algorithm helpful.
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Imbalanced Dataset Negative sampling Rate (NR)
An imbalanced dataset might have an impact on AUPR. The following experiments show more details about how the imbalance could contribute to AUPR. More details of the experiments are disclosed below: NR experiments details: Hardware Platform: GTX4080 Laptop GPU, Intel i9-13900HX, 64GB DDR5 memory Vdkey selection: We selected seq-embedding, doc2vec, and corpus-embedding, Albert for the…
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Monkeypox in 1.5 years
For MPXV, We conducted an interesting experiment over the course of one and a half years. In December 2022, we performed a search for drugs targeting the MPVX virus that we had screened and recorded the PubMed IDs and counts of co-occurrences between the virus-drug pairs. Today, one and a half years later, we performed…
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Features
We trained our sub-models on the dataset of Drugvirus info 2.0 . Advanced Features Extractors Pre-trained deep learning models were leveraged as feature extractors. Multi-Modal Deep Embeddings We leveraged pre-trained deep learning models such as Resnet50, Resnet101, EfficientNet, and Inception_Resne as image-based feature extractors, Albert, Roberta, Bert, and Gpt-2 as corpus-based transformers. We also leveraged…
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DeepSeq2Drug
An Expandable End-to-end Antiviral Drug Repurposing Framework by Multi-Modal Deep Embeddings In our manuscript, we provided an end-to-end (directly from sequence to drug) software for Antiviral Drug Repurposing. By inputting a viral sequence Fasta file (DNA sequences), and/or description to the viral, our software will first generate corresponding features and embeddings and then predict potential…
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