rnaimehaom / drug-target-prediction

Deep Mining Heterogeneous Networks to Predict Novel Drug-Target Associations

Objective:

We propose a similarity-based drug-target prediction method that enhances existing association discovery methods by using a topology-based similarity measure.

Methods:

1. NetWork: Linked Tripartite Network (LTN)
2. Similarity measure: DeepWalk
3. Inference method: DBSI, TBSI

Usage

1. Generate deepwalk index with DeepWalkMethod.java
2. Predict with Prediction.java
3. For nodes that are not listed in the network (new drugs or targets), use the similarity measures in chemicstrc and genomicsqs

Examples

please check src.edu.ucsd.dbmi.drugtarget.main.Job.java for usegae

Contact

For help or questions of using the application, please contact [email protected]

Citation

The authors appreciate to cite our published work,

Zong, N., Kim, H., Ngo, V. and Harismendy, O., 2017. Deep mining heterogeneous networks of biomedical linked data to predict novel drug–target associations. Bioinformatics, p.btx160.