New technologies have enabled the investigation of biology and human health at an
unprecedented scale and in multiple dimensions. These dimensions include a myriad of …

Over the past decade, polypharmacy instances have been common in multi-diseases
treatment. However, unwanted drug-drug interactions (DDIs) that might cause unexpected …

Abstract Motivation Drug–drug interactions (DDIs) are one of the major concerns in
pharmaceutical research. Many machine learning based methods have been proposed for …

Motivation The use of drug combinations, termed polypharmacy, is common to treat patients
with complex diseases or co-existing conditions. However, a major consequence of …

A major concern with co-administration of different drugs is the high risk of interference
between their mechanisms of action, known as adverse drug–drug interactions (DDIs) …

One of the main problems with the joint use of multiple drugs is that it may cause adverse
drug interactions and side effects that damage the body. Therefore, it is important to predict …

Motivation Adverse drug–drug interactions (DDIs) are crucial for drug research and mainly
cause morbidity and mortality. Thus, the identification of potential DDIs is essential for …

Drug–drug interactions (DDIs) are interactions with adverse effects on the body, manifested
when two or more incompatible drugs are taken together. They can be caused by the …

Biological entities are involved in intricate and complex interactions, in which uncovering the
biological information from the network concepts are of great significance. Benefiting from …

Identifying drug-target interactions will greatly narrow down the scope of search of candidate
medications, and thus can serve as the vital first step in drug discovery. Considering that in …