AIMC Topic: Drug Repositioning
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A Drug-Target Network-Based Supervised Machine Learning Repurposing Method Allowing the Use of Multiple Heterogeneous Information Sources.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
Drug-target networks have an important role in pharmaceutical innovation, drug lead discovery, and recent drug repositioning tasks. Many different in silico approaches for the identification of new drug-target interactions have been proposed, many of...
Machine Learning Approach for Predicting New Uses of Existing Drugs and Evaluation of Their Reliabilities.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
In this chapter, a new method to evaluate the reliability of predicting new uses of existing drugs was proposed. The prediction was performed with a support vector machine (SVM) using various data. Because the reliability of prediction could not be e...
A Machine-Learning-Based Drug Repurposing Approach Using Baseline Regularization.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
We present the baseline regularization model for computational drug repurposing using electronic health records (EHRs). In EHRs, drug prescriptions of various drugs are recorded throughout time for various patients. In the same time, numeric physical...
Computational Prediction of Drug-Target Interactions via Ensemble Learning.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
Therapeutic effects of drugs are mediated via interactions between them and their intended targets. As such, prediction of drug-target interactions is of great importance. Drug-target interaction prediction is especially relevant in the case of drug ...
Using Drug Expression Profiles and Machine Learning Approach for Drug Repurposing.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
The cost of new drug development has been increasing, and repurposing known medications for new indications serves as an important way to hasten drug discovery. One promising approach to drug repositioning is to take advantage of machine learning (ML...
A Drug Repurposing Method Based on Drug-Drug Interaction Networks and Using Energy Model Layouts.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
Complex network representations of reported drug-drug interactions foster computational strategies that can infer pharmacological functions which, in turn, create incentives for drug repositioning. Here, we use Gephi (a platform for complex network v...
Drug Repurposing and Artificial Intelligence: From Liaison to Marriage.
Assay and drug development technologies
Jul 1, 2018
Prediction of Human Drug Targets and Their Interactions Using Machine Learning Methods: Current and Future Perspectives.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2018
Identification of drug targets and drug target interactions are important steps in the drug-discovery pipeline. Successful computational prediction methods can reduce the cost and time demanded by the experimental methods. Knowledge of putative drug ...
How good are publicly available web services that predict bioactivity profiles for drug repurposing?
SAR and QSAR in environmental research
Oct 1, 2017
Drug repurposing provides a non-laborious and less expensive way for finding new human medicines. Computational assessment of bioactivity profiles shed light on the hidden pharmacological potential of the launched drugs. Currently, several freely ava...
Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.
Studies in health technology and informatics
Jan 1, 2015
There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sour...
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