Deep graph embedding for prioritizing synergistic anticancer drug combinations.

Jiang, Peiran; Huang, Shujun; Fu, Zhenyuan; Sun, Zexuan; Lakowski, Ted M; Hu, Pingzhao

Jiang, Peiran; Huang, Shujun; Fu, Zhenyuan; Sun, Zexuan; Lakowski, Ted M; Hu, Pingzhao.

Afiliação

Jiang P; Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada.
Huang S; Department of Bioinformatics & Systems Biology, Huazhong University of Science and Technology, Wuhan 430074, China.
Fu Z; College of Pharmacy, University of Manitoba, Winnipeg, Manitoba R3E 0T5, Canada.
Sun Z; Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Lakowski TM; Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada.
Hu P; School of Mathematics and Statistic, Wuhan University, Wuhan 430072, China.

Comput Struct Biotechnol J ; 18: 427-438, 2020.

Article em En | MEDLINE | ID: mdl-32153729

Palavras-chave

ACC, accuracy; AUC, area under the curve; CNN, convolutional neural network; Cancer; Cell line; DDS, drug-drug synergy; DNN, deep neural network; DTI, drug-target interaction; ER, estrogen receptor; FPR, false positive rate; GBM, glioblastoma multiforme; GCN, graph convolutional network; Graph convolutional network; HTS, high throughput screening; Heterogenous network; PPI, proteinprotein interaction; RF, random forest; ROC, receiver operating characteristic; SD, standard deviation; SVM, support vector machine; Synergistic drug combination; TNBC, triple negative breast cancer; TPR, true positive rate; XGBoost, extreme gradient boosting

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Canadá

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google