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Publication : briefings in bioinformatics

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Academic Journal

Nmix: a hybrid deep learning model for precise prediction of 2'-O-methylation sites based on multi-feature fusion and ensemble learning.

Authors : Geng, Yu-Qing¹ (AUTHOR); Lai, Fei-Liao¹ (AUTHOR); Luo, Hao¹ (AUTHOR)

Source: Briefings in Bioinformatics. Nov2024, Vol. 25 Issue 6, p1-14. 14p.

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Academic Journal

MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction.

Authors : Ji, Boya¹ (AUTHOR); Zou, Haitao^1,2 (AUTHOR); Xu, Liwen¹ (AUTHOR)

Source: Briefings in Bioinformatics. May2024, Vol. 25 Issue 3, p1-14. 14p.

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Academic Journal

Lactylation prediction models based on protein sequence and structural feature fusion.

Authors : Yang, Ye-Hong¹ (AUTHOR); Yang, Jun-Tao^1,2 (AUTHOR) ; Liu, Jiang-Feng^1,2 (AUTHOR)

Source: Briefings in Bioinformatics. Mar2024, Vol. 25 Issue 2, p1-8. 8p.

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A two-stage computational framework for identifying antiviral peptides and their functional types based on contrastive learning and multi-feature fusion strategy.

Authors : Guan, Jiahui^1,2 (AUTHOR); Yao, Lantian^1,3 (AUTHOR); Xie, Peilin² (AUTHOR)

Source: Briefings in Bioinformatics. May2024, Vol. 25 Issue 3, p1-13. 13p.

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Academic Journal

MFPred: prediction of ncRNA families based on multi-feature fusion.

Authors : Chen, Kai^1,2 (AUTHOR); Zhu, Xiaodong^1,2,3 (AUTHOR); Wang, Jiahao^1,2 (AUTHOR)

Source: Briefings in Bioinformatics. Sep2023, Vol. 24 Issue 5, p1-15. 15p.

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Academic Journal

Large-scale predicting protein functions through heterogeneous feature fusion.

Authors : Zheng, Rongtao¹ (AUTHOR); Huang, Zhijian¹ (AUTHOR); Deng, Lei¹ (AUTHOR)

Source: Briefings in Bioinformatics. Jul2023, Vol. 24 Issue 4, p1-12. 12p.

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CrossFuse-XGBoost: accurate prediction of the maximum recommended daily dose through multi-feature fusion, cross-validation screening and extreme gradient boosting.

Authors : Li, Qiang¹ (AUTHOR); He, Yu¹ (AUTHOR); Pan, Jianbo¹ (AUTHOR)

Source: Briefings in Bioinformatics. Jan2024, Vol. 25 Issue 1, p1-13. 13p.

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MCFF-MTDDI: multi-channel feature fusion for multi-typed drug–drug interaction prediction.

Authors : Han, Chen-Di¹ (AUTHOR); Wang, Chun-Chun^1,2 (AUTHOR); Huang, Li³ (AUTHOR)

Source: Briefings in Bioinformatics. Jul2023, Vol. 24 Issue 4, p1-15. 15p.

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Academic Journal

R5hmCFDV: computational identification of RNA 5-hydroxymethylcytosine based on deep feature fusion and deep voting.

Authors : Shi, Hongyan¹ (AUTHOR); Zhang, Shengli¹ (AUTHOR) ; Li, Xinjie¹ (AUTHOR)

Source: Briefings in Bioinformatics. Sep2022, Vol. 23 Issue 5, p1-13. 13p.

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Academic Journal

FFMAVP: a new classifier based on feature fusion and multitask learning for identifying antiviral peptides and their subclasses.

Authors : Cao, Ruifen¹ (AUTHOR); Hu, Weiling¹ (AUTHOR); Wei, Pijing² (AUTHOR)

Source: Briefings in Bioinformatics. Nov2023, Vol. 24 Issue 6, p1-10. 10p.

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فلترة النتائج

Nmix: a hybrid deep learning model for precise prediction of 2'-O-methylation sites based on multi-feature fusion and ensemble learning.

MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction.

Lactylation prediction models based on protein sequence and structural feature fusion.

A two-stage computational framework for identifying antiviral peptides and their functional types based on contrastive learning and multi-feature fusion strategy.

MFPred: prediction of ncRNA families based on multi-feature fusion.

Large-scale predicting protein functions through heterogeneous feature fusion.

CrossFuse-XGBoost: accurate prediction of the maximum recommended daily dose through multi-feature fusion, cross-validation screening and extreme gradient boosting.

MCFF-MTDDI: multi-channel feature fusion for multi-typed drug–drug interaction prediction.

R5hmCFDV: computational identification of RNA 5-hydroxymethylcytosine based on deep feature fusion and deep voting.

FFMAVP: a new classifier based on feature fusion and multitask learning for identifying antiviral peptides and their subclasses.

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