Computational Methods for Drug Repurposing

Chapter 1 Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application to Repurposing

Chapter 2 Performing an In Silico Repurposing of Existing Drugs by Combining Virtual Screening and Molecular Dynamics Simulation

Chapter 3 Repurposing Drugs Based on Evolutionary Relationships Between Targets of Approved Drugs and Proteins of Interest

Chapter 4 Drug Repositioning by Mining Adverse Event Data in ClinicalTrials.gov

Chapter 5 Transcriptomic Data Mining and Repurposing for Computational Drug Discovery

Chapter 6 Network-Based Drug Repositioning: Approaches, Resources, and Research Directions

Chapter 7 A Computational Bipartite Graph-Based Drug Repurposing Method

Chapter 8 Implementation of a Pipeline Using Disease-Disease Associations for Computational Drug Repurposing

Chapter 9 An Application of Computational Drug Repurposing Based on Transcriptomic Signatures

Chapter 10 Drug-Induced Expression-Based Computational Repurposing of Small Molecules Affecting Transcription Factor Activity

Chapter 11 A Drug Repurposing Method Based on Drug-Drug Interaction Networks and Using Energy Model Layouts

Chapter 12 Integrating Biological Networks for Drug Target Prediction and Prioritization

Chapter 13 Using Drug Expression Profiles and Machine Learning Approach for Drug Repurposing

Chapter 14 Computational Prediction of Drug-Target Interactions via Ensemble Learning

Chapter 15 A Machine-Learning-Based Drug Repurposing Approach Using Baseline Regularization

Chapter 16 Machine Learning Approach for Predicting New Uses of Existing Drugs and Evaluation of Their Reliabilities

Chapter 17 A Drug-Target Network-Based Supervised Machine Learning Repurposing Method Allowing the Use of Multiple Heterogeneous Information Sources

Chapter 18 Heter-LP: A Heterogeneous Label Propagation Method for Drug Repositioning

Chapter 19 Tripartite Network-Based Repurposing Method Using Deep Learning to Compute Similarities for Drug-Target Prediction