Drug repositioning based on individual bi-random walks on a heterogeneous network
Abstract Background Traditional drug research and development is high cost, time-consuming and risky. Computationally identifying new indications for existing drugs, referred as drug repositioning, greatly reduces the cost and attracts ever-increasing research interests. Many network-based methods h...
Main Authors: | Yuehui Wang, Maozu Guo, Yazhou Ren, Lianyin Jia, Guoxian Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2019-12-01
|
Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12859-019-3117-6 |
Similar Items
-
Guiding Drug Repositioning for Cancers Based on Drug Similarity Networks
by: Shimei Qin, et al.
Published: (2023-01-01) -
MNBDR: A Module Network Based Method for Drug Repositioning
by: He-Gang Chen, et al.
Published: (2020-12-01) -
Identifying Small Molecule-miRNA Associations Based on Credible Negative Sample Selection and Random Walk
by: Fuxing Liu, et al.
Published: (2020-03-01) -
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning
by: Maha A. Thafar, et al.
Published: (2021-09-01) -
Drug-Disease Association Prediction Using Heterogeneous Networks for Computational Drug Repositioning
by: Yoonbee Kim, et al.
Published: (2022-10-01)