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StableDNAm: towards a stable and efficient model for predicting DNA methylation based on adaptive feature correction learning

BMC genomics, 2023-12, Vol.24 (1), p.742-742, Article 742

2023

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An efficient model for predicting human diseases through miRNA based on multiple-types of contrastive learning

Frontiers in microbiology, 2023, Vol.14, p.1325001-1325001

2023

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Prediction of miRNA-disease associations in microbes based on graph convolutional networks and autoencoders

Frontiers in microbiology, 2023-04, Vol.14, p.1170559-1170559

2023

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Joint masking and self-supervised strategies for inferring small molecule-miRNA associations

Molecular therapy. Nucleic acids, 2024-03, Vol.35 (1), p.102103-102103, Article 102103

2024

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Fusion of multi-source relationships and topology to infer lncRNA-protein interactions

Molecular therapy. Nucleic acids, 2024-06, Vol.35 (2), p.102187-102187, Article 102187

2024

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DPB-NBFnet: Using neural Bellman-Ford networks to predict DNA-protein binding

Frontiers in pharmacology, 2022-10, Vol.13, p.1018294-1018294

2022

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Prediction of lncRNA-Protein Interactions via the Multiple Information Integration

Frontiers in bioengineering and biotechnology, 2021-02, Vol.9, p.647113-647113

2021

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HCFS: A Density Peak Based Clustering Algorithm Employing A Hierarchical Strategy

IEEE access, 2019, Vol.7, p.74612-74624

2019

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MVTLR-HCFS: Density Peak Algorithm Based on Multi-View and Tensor Low Rank Expression

IEEE access, 2021, Vol.9, p.14619-14629

2021

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Joint deep autoencoder and subgraph augmentation for inferring microbial responses to drugs

Briefings in bioinformatics, 2023-11, Vol.25 (1)

2023

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GraphADT: Empowering interpretable predictions of acute dermal toxicity with Multi-View graph pooling and structure remapping

Bioinformatics (Oxford, England), 2024-07, Vol.40 (7)

2024

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Predicting miRNA-lncRNA interactions on plant datasets based on bipartite network embedding method

Methods (San Diego, Calif.), 2022-11, Vol.207, p.97-102

2022

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Predicting ncRNA–protein interactions based on dual graph convolutional network and pairwise learning

Briefings in bioinformatics, 2022-09, Vol.23 (5)

2022

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A model for predicting ncRNA–protein interactions based on graph neural networks and community detection

Methods (San Diego, Calif.), 2022-11, Vol.207, p.74-80

2022

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Revisiting drug–protein interaction prediction: a novel global–local perspective

Bioinformatics (Oxford, England), 2024-05, Vol.40 (5)

2024

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ML-NPI: Predicting Interactions between Noncoding RNA and Protein Based on Meta-Learning in a Large-Scale Dynamic Graph

Journal of chemical information and modeling, 2024-04, Vol.64 (7), p.2912-2920

2024

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ECD-CDGI: An efficient energy-constrained diffusion model for cancer driver gene identification

PLoS computational biology, 2024-08, Vol.20 (8), p.e1012400

2024

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Efficient Deep Model Ensemble Framework for Drug-Target Interaction Prediction

The journal of physical chemistry letters, 2024-08, Vol.15 (30), p.7681-7693

2024

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SGAE-MDA: Exploring the MiRNA-disease associations in herbal medicines based on semi-supervised graph autoencoder

Methods (San Diego, Calif.), 2024-01, Vol.221, p.73-81

2024

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GCFMCL: predicting miRNA-drug sensitivity using graph collaborative filtering and multi-view contrastive learning

Briefings in bioinformatics, 2023-07, Vol.24 (4)

2023

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Diff-AMP: tailored designed antimicrobial peptide framework with all-in-one generation, identification, prediction and optimization

Briefings in bioinformatics, 2024-01, Vol.25 (2)

2024

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MHAM-NPI: Predicting ncRNA-protein interactions based on multi-head attention mechanism

Computers in biology and medicine, 2023-09, Vol.163, p.107143-107143, Article 107143

2023

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Multi-source data integration for explainable miRNA-driven drug discovery

Future generation computer systems, 2024-11, Vol.160, p.109-119

2024

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MultiCBlo: Enhancing predictions of compound-induced inhibition of cardiac ion channels with advanced multimodal learning

International journal of biological macromolecules, 2024-09, Vol.276 (Pt 2), p.133825, Article 133825

2024

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MS-BACL: enhancing metabolic stability prediction through bond graph augmentation and contrastive learning

Briefings in bioinformatics, 2024-03, Vol.25 (3)

2024

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StableDNAm: towards a stable and efficient model for predicting DNA methylation based on adaptive feature correction learning

An efficient model for predicting human diseases through miRNA based on multiple-types of contrastive learning

Prediction of miRNA-disease associations in microbes based on graph convolutional networks and autoencoders

Joint masking and self-supervised strategies for inferring small molecule-miRNA associations

Fusion of multi-source relationships and topology to infer lncRNA-protein interactions

DPB-NBFnet: Using neural Bellman-Ford networks to predict DNA-protein binding

Prediction of lncRNA-Protein Interactions via the Multiple Information Integration

HCFS: A Density Peak Based Clustering Algorithm Employing A Hierarchical Strategy

MVTLR-HCFS: Density Peak Algorithm Based on Multi-View and Tensor Low Rank Expression

Joint deep autoencoder and subgraph augmentation for inferring microbial responses to drugs

GraphADT: Empowering interpretable predictions of acute dermal toxicity with Multi-View graph pooling and structure remapping

Predicting miRNA-lncRNA interactions on plant datasets based on bipartite network embedding method

Predicting ncRNA–protein interactions based on dual graph convolutional network and pairwise learning

A model for predicting ncRNA–protein interactions based on graph neural networks and community detection

Revisiting drug–protein interaction prediction: a novel global–local perspective

ML-NPI: Predicting Interactions between Noncoding RNA and Protein Based on Meta-Learning in a Large-Scale Dynamic Graph

ECD-CDGI: An efficient energy-constrained diffusion model for cancer driver gene identification

Efficient Deep Model Ensemble Framework for Drug-Target Interaction Prediction

SGAE-MDA: Exploring the MiRNA-disease associations in herbal medicines based on semi-supervised graph autoencoder

GCFMCL: predicting miRNA-drug sensitivity using graph collaborative filtering and multi-view contrastive learning

Diff-AMP: tailored designed antimicrobial peptide framework with all-in-one generation, identification, prediction and optimization

MHAM-NPI: Predicting ncRNA-protein interactions based on multi-head attention mechanism

Multi-source data integration for explainable miRNA-driven drug discovery

MultiCBlo: Enhancing predictions of compound-induced inhibition of cardiac ion channels with advanced multimodal learning

MS-BACL: enhancing metabolic stability prediction through bond graph augmentation and contrastive learning

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