AIMC Topic: Drug Repositioning

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Predicting Drug-Disease Associations via Using Gaussian Interaction Profile and Kernel-Based Autoencoder.

BioMed research international
Computational drug repositioning, designed to identify new indications for existing drugs, significantly reduced the cost and time involved in drug development. Prediction of drug-disease associations is promising for drug repositioning. Recent years...

Improved Prediction of Drug-Target Interactions Using Self-Paced Learning with Collaborative Matrix Factorization.

Journal of chemical information and modeling
Identifying drug-target interactions (DTIs) plays an important role in the field of drug discovery, drug side-effects, and drug repositioning. However, in vivo or biochemical experimental methods for identifying new DTIs are extremely expensive and t...

HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods.

Scientific reports
Recent data indicate that up-to 30-40% of cancers can be prevented by dietary and lifestyle measures alone. Herein, we introduce a unique network-based machine learning platform to identify putative food-based cancer-beating molecules. These have bee...

Using artificial intelligence methods to speed up drug discovery.

Expert opinion on drug discovery
: Drug discovery is the process through which potential new compounds are identified by means of biology, chemistry, and pharmacology. Due to the high complexity of genomic data, AI techniques are increasingly needed to help reduce this and aid the a...

Drug repositioning of herbal compounds via a machine-learning approach.

BMC bioinformatics
BACKGROUND: Drug repositioning, also known as drug repurposing, defines new indications for existing drugs and can be used as an alternative to drug development. In recent years, the accumulation of large volumes of information related to drugs and d...

DrugR+: A comprehensive relational database for drug repurposing, combination therapy, and replacement therapy.

Computers in biology and medicine
Drug repurposing or repositioning, which introduces new applications of the existing drugs, is an emerging field in drug discovery scope. To enhance the success rate of the research and development (R&D) process in a cost- and time-effective manner, ...

Drug repurposing in oncology: Compounds, pathways, phenotypes and computational approaches for colorectal cancer.

Biochimica et biophysica acta. Reviews on cancer
The strategy of using existing drugs originally developed for one disease to treat other indications has found success across medical fields. Such drug repurposing promises faster access of drugs to patients while reducing costs in the long and diffi...

Exploiting machine learning for end-to-end drug discovery and development.

Nature materials
A variety of machine learning methods such as naive Bayesian, support vector machines and more recently deep neural networks are demonstrating their utility for drug discovery and development. These leverage the generally bigger datasets created from...

Serendipity-A Machine-Learning Application for Mining Serendipitous Drug Usage From Social Media.

IEEE transactions on nanobioscience
Serendipitous drug usage refers to the unexpected relief of comorbid diseases or symptoms when taking medication for a different known indication. Historically, serendipity has contributed significantly to identifying many new drug indications. If pa...

Building the drug-GO function network to screen significant candidate drugs for myasthenia gravis.

PloS one
Myasthenia gravis (MG) is an autoimmune disease. In recent years, considerable evidence has indicated that Gene Ontology (GO) functions, especially GO-biological processes, have important effects on the mechanisms and treatments of different diseases...