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Cited in SCI: 72
SBSM-Pro: support bio-sequence machine for proteins
Wang, Yizheng; Zhai, Yixiao; Ding, Yijie; Zou, Quan
Sci China Inf Sci, 2024, 67(11): 212106
Keywords: protein classification; machine learning; multiple kernel learning; sequence alignment
Cite as: Wang Y Z, Zhai Y X, Ding Y J, et al. SBSM-Pro: support bio-sequence machine for proteins. Sci China Inf Sci, 2024, 67(11): 212106, doi: 10.1007/s11432-024-4171-9
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Cited in SCI: 18
BioKG-CMI: a multi-source feature fusion model based on biological knowledge graph for predicting circRNA-miRNA interactions
Wei, Mengmeng; Wang, Lei; Li, Yang; Li, Zhengwei; Zhao, Bowei; Su, Xiaorui; Wei, Yu; You, Zhuhong
Sci China Inf Sci, 2024, 67(8): 189104
Keywords: circRNA-miRNA interaction; biological knowledge graph; subcellular localization; multi-source feature fusion; natural language processing
Cite as: Wei M M, Wang L, Li Y, et al. BioKG-CMI: a multi-source feature fusion model based on biological knowledge graph for predicting circRNA-miRNA interactions. Sci China Inf Sci, 2024, 67(8): 189104, doi: 10.1007/s11432-024-4098-3
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Keywords: therapeutic peptide prediction; multi-label classification; pretrained protein language model; multi-label supervised contrastive learning
Cite as: Yan K, Lv H W, Shao J Y, et al. TPpred-SC: multi-functional therapeutic peptide prediction based on multi-label supervised contrastive learning. Sci China Inf Sci, 2024, 67(11): 212105, doi: 10.1007/s11432-024-4147-8
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Cited in SCI: 5
Integrating sequence and graph information for enhanced drug-target affinity prediction
He, Haohuai; Chen, Guanxing; Chen, Calvin Yu-Chian
Sci China Inf Sci, 2024, 67(2): 129101
Keywords: drug-target affinity; hybrid graph neural network; adaptive features; explainability; catalytic triad
Cite as: He H H, Chen G X, Chen C Y-C. Integrating sequence and graph information for enhanced drug-target affinity prediction. Sci China Inf Sci, 2024, 67(2): 129101, doi: 10.1007/s11432-022-3793-7
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Keywords: heterogeneous graph learning; multiple types of disease-associated RNA identification; disease prognosis and therapy; systematic pathogenesis analysis; hepatocellular carcinoma
Cite as: Zhang W X, Wei H, Zhang W J, et al. Multiple types of disease-associated RNAs identification for disease prognosis and therapy using heterogeneous graph learning. Sci China Inf Sci, 2024, 67(8): 189103, doi: 10.1007/s11432-024-4100-7
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Keywords: Budd-Chiari syndrome; attention mechanism; multi-hop graph learning; high-risk factors; graph neural networks
Cite as: Wang L, Li S L, Su X R, et al. Prediction of Budd-Chiari syndrome based on attention mechanisms of high-risk factors in multi-hop graph learning. Sci China Inf Sci, 2025, 68(7): 179102, doi: 10.1007/s11432-024-4358-3
Special Topic: AI for Biology
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OntoGene: knowledge-enhanced BERT for promoter identification
Li Y, Gao M L, Bian J L, et al
Sci China Inf Sci, 2025, 68(7): 170106
Keywords: promoter identification; knowledge enhancement; knowledge graph; BERT
Cite as: Li Y, Gao M L, Bian J L, et al. OntoGene: knowledge-enhanced BERT for promoter identification. Sci China Inf Sci, 2025, 68(7): 170106, doi: 10.1007/s11432-024-4481-9
Special Topic: AI for Biology
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Keywords: biomedical research; AI for research; large language models; multi-agent systems; automation
Cite as: Luo Y, Shi L H, Li Y H, et al. From intention to implementation: automating biomedical research via LLMs. Sci China Inf Sci, 2025, 68(7): 170105, doi: 10.1007/s11432-024-4485-0
Special Topic: AI for Biology
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Molecular pretraining models towards molecular property prediction
Qiao J B, Gao W J, Jin J R, et al
Sci China Inf Sci, 2025, 68(7): 170104
Keywords: molecular pretraining models; molecular property prediction; graph neural network; GNN; graph Transformer; PubChem; MoleculeNet
Cite as: Qiao J B, Gao W J, Jin J R, et al. Molecular pretraining models towards molecular property prediction. Sci China Inf Sci, 2025, 68(7): 170104, doi: 10.1007/s11432-024-4457-2
Special Topic: AI for Biology
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Self-supervised learning in drug discovery
Chen Y Y, Wang Z X, Wang J M, et al
Sci China Inf Sci, 2025, 68(7): 170103
Keywords: drug discovery; self-supervised learning; drug representation
Cite as: Chen Y Y, Wang Z X, Wang J M, et al. Self-supervised learning in drug discovery. Sci China Inf Sci, 2025, 68(7): 170103, doi: 10.1007/s11432-024-4453-4
Special Topic: AI for Biology
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Keywords: artificial intelligence; deep learning; drug research; drug repositioning; genomic data
Cite as: Qi R, Liu S J, Hui X Q, et al. AI in drug development: advances in response, combination therapy, repositioning, and molecular design. Sci China Inf Sci, 2025, 68(7): 170102, doi: 10.1007/s11432-024-4461-0
Special Topic: AI for Biology
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Keywords: biological sequence and multimodal data; large language model; genome; transcriptome; proteome
Cite as: Wang T, Luo Z Y. Large language models transform biological research: from architecture to utilization. Sci China Inf Sci, 2025, 68(7): 170101, doi: 10.1007/s11432-024-4466-3
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TaxDiff: taxonomic-guided diffusion model for protein sequence generation
Lin, Zongying; Li, Hao; Lv, Liuzhenghao; Wang, Yu; Lin, Bin; Zhang, Junwu; Chen, Zijun; Chen, Calvin Yu-Chian; Yuan, Li; Tian, Yonghong
Sci China Inf Sci, 2025, 68(4): 149101
Keywords: controlled protein sequence generation; protein sequence design; diffusion model; generative models; protein sequence generation
Cite as: Lin Z Y, Li H, Lv L Z H, et al. TaxDiff: taxonomic-guided diffusion model for protein sequence generation. Sci China Inf Sci, 2025, 68(4): 149101, doi: 10.1007/s11432-024-4296-6
