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Identifying drug–target interactions based on graph convolutional network and deep neural network

Briefings in bioinformatics, 2021-03, Vol.22 (2), p.2141-2150

2021

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CNN-DDI: a learning-based method for predicting drug-drug interactions using convolution neural networks

BMC bioinformatics, 2022-03, Vol.23 (Suppl 1), p.88-88, Article 88

2022

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A multi-network integration approach for measuring disease similarity based on ncRNA regulation and heterogeneous information

BMC bioinformatics, 2022-03, Vol.23 (Suppl 1), p.89-89, Article 89

2022

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DRACP: a novel method for identification of anticancer peptides

BMC bioinformatics, 2020-12, Vol.21 (Suppl 16), p.559-559, Article 559

2020

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Identifying diseases-related metabolites using random walk

BMC bioinformatics, 2018-04, Vol.19 (Suppl 5), p.116-116, Article 116

2018

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Identifying Alzheimer's disease-related proteins by LRRGD

BMC bioinformatics, 2019-11, Vol.20 (Suppl 18), p.570-570, Article 570

2019

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Integrate GWAS, eQTL, and mQTL Data to Identify Alzheimer's Disease-Related Genes

Frontiers in genetics, 2019-10, Vol.10, p.1021-1021

2019

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deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index

Genome Biology, 2019-12, Vol.20 (1), p.274-274, Article 274

2019

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Peptide-Major Histocompatibility Complex Class I Binding Prediction Based on Deep Learning With Novel Feature

Frontiers in genetics, 2019-11, Vol.10, p.1191-1191

2019

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Identification of Alzheimer's Disease-Related Genes Based on Data Integration Method

Frontiers in genetics, 2019-01, Vol.9, p.703

2019

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A Review of Drug Side Effect Identification Methods

Current pharmaceutical design, 2020-01, Vol.26 (26), p.3096

2020

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LncDisAP: a computation model for LncRNA-disease association prediction based on multiple biological datasets

BMC bioinformatics, 2019-12, Vol.20 (Suppl 16), p.582-11, Article 582

2019

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Prioritizing candidate diseases-related metabolites based on literature and functional similarity

BMC bioinformatics, 2019-11, Vol.20 (Suppl 18), p.574-574, Article 574

2019

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Predicting circRNA-Disease Associations Based on circRNA Expression Similarity and Functional Similarity

Frontiers in genetics, 2019-09, Vol.10, p.832-832

2019

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Explore potential disease related metabolites based on latent factor model

BMC genomics, 2022-04, Vol.23 (Suppl 1), p.269-269, Article 269

2022

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Integration of multiple-omics data to reveal the shared genetic architecture of educational attainment, intelligence, cognitive performance, and Alzheimer's disease

Frontiers in genetics, 2023-10, Vol.14, p.1243879-1243879

2023

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Human mitochondrial genome compression using machine learning techniques

Human genomics, 2019-10, Vol.13 (Suppl 1), p.49-49, Article 49

2019

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Identifying Protein Biomarkers in Blood for Alzheimer's Disease

Frontiers in cell and developmental biology, 2020-06, Vol.8, p.472-472

2020

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Prediction for High Risk Clinical Symptoms of Epilepsy Based on Deep Learning Algorithm

IEEE access, 2018, Vol.6, p.77596-77605

2018

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Enhancement and Imputation of Peak Signal Enables Accurate Cell-Type Classification in scATAC-seq

Frontiers in genetics, 2021-04, Vol.12, p.658352-658352

2021

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DeepGP: An Integrated Deep Learning Method for Endocrine Disease Gene Prediction Using Omics Data

Frontiers in cell and developmental biology, 2021-07, Vol.9, p.700061-700061

2021

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Psi-Caller: A Lightweight Short Read-Based Variant Caller With High Speed and Accuracy

Frontiers in cell and developmental biology, 2021-08, Vol.9, p.731424-731424

2021

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BdBG: a bucket-based method for compressing genome sequencing data with dynamic de Bruijn graphs

PeerJ (San Francisco, CA), 2018-10, Vol.6, p.e5611-e5611, Article e5611

2018

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KGE-UNIT: toward the unification of molecular interactions prediction based on knowledge graph and multi-task learning on drug discovery

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

2024

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MRTFB regulates the expression of NOMO1 in colon

Proceedings of the National Academy of Sciences - PNAS, 2020-04, Vol.117 (14), p.7568-7569

2020

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Identifying drug–target interactions based on graph convolutional network and deep neural network

CNN-DDI: a learning-based method for predicting drug-drug interactions using convolution neural networks

A multi-network integration approach for measuring disease similarity based on ncRNA regulation and heterogeneous information

DRACP: a novel method for identification of anticancer peptides

Identifying diseases-related metabolites using random walk

Identifying Alzheimer's disease-related proteins by LRRGD

Integrate GWAS, eQTL, and mQTL Data to Identify Alzheimer's Disease-Related Genes

deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index

Peptide-Major Histocompatibility Complex Class I Binding Prediction Based on Deep Learning With Novel Feature

Identification of Alzheimer's Disease-Related Genes Based on Data Integration Method

A Review of Drug Side Effect Identification Methods

LncDisAP: a computation model for LncRNA-disease association prediction based on multiple biological datasets

Prioritizing candidate diseases-related metabolites based on literature and functional similarity

Predicting circRNA-Disease Associations Based on circRNA Expression Similarity and Functional Similarity

Explore potential disease related metabolites based on latent factor model

Integration of multiple-omics data to reveal the shared genetic architecture of educational attainment, intelligence, cognitive performance, and Alzheimer's disease

Human mitochondrial genome compression using machine learning techniques

Identifying Protein Biomarkers in Blood for Alzheimer's Disease

Prediction for High Risk Clinical Symptoms of Epilepsy Based on Deep Learning Algorithm

Enhancement and Imputation of Peak Signal Enables Accurate Cell-Type Classification in scATAC-seq

DeepGP: An Integrated Deep Learning Method for Endocrine Disease Gene Prediction Using Omics Data

Psi-Caller: A Lightweight Short Read-Based Variant Caller With High Speed and Accuracy

BdBG: a bucket-based method for compressing genome sequencing data with dynamic de Bruijn graphs

KGE-UNIT: toward the unification of molecular interactions prediction based on knowledge graph and multi-task learning on drug discovery

MRTFB regulates the expression of NOMO1 in colon

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