Drug-target interaction (DTI) prediction plays a crucial role in drug repositioning and virtual
drug screening. Most DTI prediction methods cast the problem as a binary classification task …

Drug–target interaction (DTI) prediction is a crucial step in drug discovery and repositioning
as it reduces experimental validation costs if done right. Thus, developing in-silico methods …

Linked data and bio-ontologies enabling knowledge representation, standardization, and
dissemination are an integral part of developing biological and biomedical databases. That …

Late-stage drug development failures are usually a consequence of ineffective targets. Thus,
proper target identification is needed, which may be possible using computational …

The decoding of the human genome, completed two decades ago, marked a revolutionary
moment in biology by introducing a vast amount of data. This avalanche of information …

The end-to-end process in the discovery of drugs involves therapeutic candidate
identification, validation of identified targets, identification of hit compound series, lead …

Drug–target interaction (DTI) identification is a complex process that is time-consuming,
costly and frequently inefficient, with a low success rate, especially with wet-experimental …

Biomedical knowledge is represented in structured databases and published in biomedical
literature, and different computational approaches have been developed to exploit each type …

Drug‐target interactions provide useful information for biomedical drug discovery as well as
drug development. However, it is costly and time consuming to find drug‐target interactions …

The growth in academic and scientific publications has increased very rapidly. Researchers
must choose a representative and significant literature for their research, which has become …