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iCDA-CGR: Identification of circRNA-disease associations based on Chaos Game Representation

PLoS computational biology, 2020-05, Vol.16 (5), p.e1007872-e1007872

2020

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RPI-SE: a stacking ensemble learning framework for ncRNA-protein interactions prediction using sequence information

BMC bioinformatics, 2020-02, Vol.21 (1), p.60-60, Article 60

2020

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scCorrector: a robust method for integrating multi-study single-cell data

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

2024

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scInterpreter: a knowledge-regularized generative model for interpretably integrating scRNA-seq data

BMC bioinformatics, 2023-12, Vol.24 (1), p.481-481, Article 481

2023

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Comparison of myocardial microcirculatory perfusion after catheter‐administered intracoronary thrombolysis with anisodamine versus standard thrombus aspiration in patients with ST‐elevation myocardial infarction

Catheterization and cardiovascular interventions, 2019-02, Vol.93 (S1), p.839-845

2019

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MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm

Briefings in bioinformatics, 2021-03, Vol.22 (2), p.2085-2095

2021

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A learning-based method to predict LncRNA-disease associations by combining CNN and ELM

BMC bioinformatics, 2022-03, Vol.22 (Suppl 5), p.622-622, Article 622

2022

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A Novel Method to Predict Drug-Target Interactions Based on Large-Scale Graph Representation Learning

Cancers, 2021-04, Vol.13 (9), p.2111

2021

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A Learning-Based Method for LncRNA-Disease Association Identification Combing Similarity Information and Rotation Forest

iScience, 2019-09, Vol.19, p.786-795

2019

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Prediction of drug-target interactions from multi-molecular network based on LINE network representation method

Journal of translational medicine, 2020-09, Vol.18 (1), p.347-11, Article 347

2020

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Construction and Analysis of Molecular Association Network by Combining Behavior Representation and Node Attributes

Frontiers in genetics, 2019-11, Vol.10, p.1106-1106

2019

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Prediction of Drug–Target Interactions From Multi-Molecular Network Based on Deep Walk Embedding Model

Frontiers in bioengineering and biotechnology, 2020-06, Vol.8

2020

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Construction and Comprehensive Analysis of a Molecular Association Network via lncRNA-miRNA -Disease-Drug-Protein Graph

Cells (Basel, Switzerland), 2019-08, Vol.8 (8), p.866

2019

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iMDA-BN: Identification of miRNA-disease associations based on the biological network and graph embedding algorithm

Computational and structural biotechnology journal, 2020-01, Vol.18, p.2391-2400

2020

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GraphCPIs: A novel graph-based computational model for potential compound-protein interactions

Molecular therapy. Nucleic acids, 2023-06, Vol.32, p.721-728

2023

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Learning Representations to Predict Intermolecular Interactions on Large-Scale Heterogeneous Molecular Association Network

iScience, 2020-07, Vol.23 (7), p.101261-101261, Article 101261

2020

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MIPDH: A Novel Computational Model for Predicting microRNA–mRNA Interactions by DeepWalk on a Heterogeneous Network

ACS omega, 2020-07, Vol.5 (28), p.17022-17032

2020

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A learning based framework for diverse biomolecule relationship prediction in molecular association network

Communications biology, 2020-03, Vol.3 (1), p.118, Article 118

2020

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Bioentity2vec: Attribute- and behavior-driven representation for predicting multi-type relationships between bioentities

Gigascience, 2020-06, Vol.9 (6)

2020

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Effects of Levosimendan on Right Ventricular Function in Patients with Acute Decompensated Heart Failure

Acta Cardiologica Sinica, 2019-11, Vol.35 (6), p.585-591

2019

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Predicting the Sequence Specificities of DNA-Binding Proteins by DNA Fine-Tuned Language Model With Decaying Learning Rates

IEEE/ACM transactions on computational biology and bioinformatics, 2023-01, Vol.20 (1), p.616-624

2023

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IEEE_Xplore

Integrative Construction and Analysis of Molecular Association Network in Human Cells by Fusing Node Attribute and Behavior Information

Molecular therapy. Nucleic acids, 2020-03, Vol.19, p.498-506

2020

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Learning Representation of Molecules in Association Network for Predicting Intermolecular Associations

IEEE/ACM transactions on computational biology and bioinformatics, 2021-11, Vol.18 (6), p.2546-2554

2021

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IEEE_Xplore

Preventive effects of anisodamine against contrast-induced nephropathy in type 2 diabetics with renal insufficiency undergoing coronary angiography or angioplasty

Chinese medical journal, 2012-10, Vol.125 (19), p.3368-3372

2012

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Prediction of contrast-induced nephropathy in diabetics undergoing elective percutaneous coronary intervention： role of the ratio of contrast medium volume to estimated glomerular filtration rate

Chinese medical journal, 2011-03, Vol.124 (6), p.892-896

2011

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iCDA-CGR: Identification of circRNA-disease associations based on Chaos Game Representation

RPI-SE: a stacking ensemble learning framework for ncRNA-protein interactions prediction using sequence information

scCorrector: a robust method for integrating multi-study single-cell data

scInterpreter: a knowledge-regularized generative model for interpretably integrating scRNA-seq data

Comparison of myocardial microcirculatory perfusion after catheter‐administered intracoronary thrombolysis with anisodamine versus standard thrombus aspiration in patients with ST‐elevation myocardial infarction

MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm

A learning-based method to predict LncRNA-disease associations by combining CNN and ELM

A Novel Method to Predict Drug-Target Interactions Based on Large-Scale Graph Representation Learning

A Learning-Based Method for LncRNA-Disease Association Identification Combing Similarity Information and Rotation Forest

Prediction of drug-target interactions from multi-molecular network based on LINE network representation method

Construction and Analysis of Molecular Association Network by Combining Behavior Representation and Node Attributes

Prediction of Drug–Target Interactions From Multi-Molecular Network Based on Deep Walk Embedding Model

Construction and Comprehensive Analysis of a Molecular Association Network via lncRNA-miRNA -Disease-Drug-Protein Graph

iMDA-BN: Identification of miRNA-disease associations based on the biological network and graph embedding algorithm

GraphCPIs: A novel graph-based computational model for potential compound-protein interactions

Learning Representations to Predict Intermolecular Interactions on Large-Scale Heterogeneous Molecular Association Network

MIPDH: A Novel Computational Model for Predicting microRNA–mRNA Interactions by DeepWalk on a Heterogeneous Network

A learning based framework for diverse biomolecule relationship prediction in molecular association network

Bioentity2vec: Attribute- and behavior-driven representation for predicting multi-type relationships between bioentities

Effects of Levosimendan on Right Ventricular Function in Patients with Acute Decompensated Heart Failure

Predicting the Sequence Specificities of DNA-Binding Proteins by DNA Fine-Tuned Language Model With Decaying Learning Rates

Integrative Construction and Analysis of Molecular Association Network in Human Cells by Fusing Node Attribute and Behavior Information

Learning Representation of Molecules in Association Network for Predicting Intermolecular Associations

Preventive effects of anisodamine against contrast-induced nephropathy in type 2 diabetics with renal insufficiency undergoing coronary angiography or angioplasty

Prediction of contrast-induced nephropathy in diabetics undergoing elective percutaneous coronary intervention： role of the ratio of contrast medium volume to estimated glomerular filtration rate

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