Predicting circRNA-drug sensitivity associations via graph attention auto-encoder

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1471-2105

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Predicting circRNA-drug sensitivity associations via graph attention auto-encoder ; volume:23 ; number:1 ; day:4 ; month:5 ; year:2022 ; pages:1-15 ; date:12.2022
BMC bioinformatics ; 23, Heft 1 (4.5.2022), 1-15, 12.2022

Creator: Deng, Lei
Liu, Zixuan
Qian, Yurong
Zhang, Jingpu

Contributor: SpringerLink (Online service)

DOI: 10.1186/s12859-022-04694-y

URN: urn:nbn:de:101:1-2022071221141920038102

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:32 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Show original at data provider

Associated

Deng, Lei
Liu, Zixuan
Qian, Yurong
Zhang, Jingpu
SpringerLink (Online service)

Other Objects (12)

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction

CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network

Divergent models of soil organic carbon sequestration related to vegetation restoration

Interactions between Blastocystis subtype ST4 and gut microbiota in vitro

SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost

MSCFS: inferring circRNA functional similarity based on multiple data sources

XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

Correction to: XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

CMAGN: circRNA–miRNA association prediction based on graph attention auto-encoder and network consistency projection

Aufsatzsammlung

Quan kuan guan jie zhi huan : zhi huan ji shu he ju bu bing fa zheng

Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction

CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network

Divergent models of soil organic carbon sequestration related to vegetation restoration

Interactions between Blastocystis subtype ST4 and gut microbiota in vitro

SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost

MSCFS: inferring circRNA functional similarity based on multiple data sources

XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

Correction to: XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

CMAGN: circRNA–miRNA association prediction based on graph attention auto-encoder and network consistency projection

Aufsatzsammlung

Quan kuan guan jie zhi huan : zhi huan ji shu he ju bu bing fa zheng

Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction

CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network

Divergent models of soil organic carbon sequestration related to vegetation restoration

Interactions between Blastocystis subtype ST4 and gut microbiota in vitro

SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost

MSCFS: inferring circRNA functional similarity based on multiple data sources

XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

Correction to: XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

CMAGN: circRNA–miRNA association prediction based on graph attention auto-encoder and network consistency projection

Aufsatzsammlung

Quan kuan guan jie zhi huan : zhi huan ji shu he ju bu bing fa zheng

Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.

Predicting circRNA-drug sensitivity associations via graph attention auto-encoder

Object Details

References and Relationships

Contributors, Places and Time

Further information

Data provider

Associated

Other Objects (12)

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction

CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network

Divergent models of soil organic carbon sequestration related to vegetation restoration

Interactions between Blastocystis subtype ST4 and gut microbiota in vitro

SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost

MSCFS: inferring circRNA functional similarity based on multiple data sources

XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

Correction to: XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

CMAGN: circRNA–miRNA association prediction based on graph attention auto-encoder and network consistency projection

Quan kuan guan jie zhi huan : zhi huan ji shu he ju bu bing fa zheng

Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction

CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network

Divergent models of soil organic carbon sequestration related to vegetation restoration

Interactions between Blastocystis subtype ST4 and gut microbiota in vitro

SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost

MSCFS: inferring circRNA functional similarity based on multiple data sources

XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

Correction to: XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

CMAGN: circRNA–miRNA association prediction based on graph attention auto-encoder and network consistency projection

Quan kuan guan jie zhi huan : zhi huan ji shu he ju bu bing fa zheng

Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction

CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network

Divergent models of soil organic carbon sequestration related to vegetation restoration

Interactions between Blastocystis subtype ST4 and gut microbiota in vitro

SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost

MSCFS: inferring circRNA functional similarity based on multiple data sources

XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

Correction to: XGBCDA: a multiple heterogeneous networks-based method for predicting circRNA-disease associations

CMAGN: circRNA–miRNA association prediction based on graph attention auto-encoder and network consistency projection

Quan kuan guan jie zhi huan : zhi huan ji shu he ju bu bing fa zheng

Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

Related objects

Reset password