Advances over the past decade in drug discovery technologies have not yet led to an
increase in productivity. We analyzed the reasons that have led to this juncture and identify …

The rapid development of techniques in the area of genome analysis has facilitated
identification of new pharmacogenomic biomarkers that can provide predictive tools for …

Genomic studies are producing large databases of molecular information on cancers and
other cell and tissue types. Hence, we have the opportunity to link these accumulating data …

Pharmacogenomics requires the integration and analysis of genomic, molecular, cellular,
and clinical data, and it thus offers a remarkable set of challenges to biomedical informatics …

Computational prediction of drug–target interactions (DTIs) has become an essential task in
the drug discovery process. It narrows down the search space for interactions by suggesting …

Pharmacogenomics holds great promise for the development of biomarkers of drug
response and the design of new therapeutic options, which are key challenges in precision …

Predicting drug–target interaction using computational approaches is an important step in
drug discovery and repositioning. To predict whether there will be an interaction between a …

The increase in drug research output from patent applications, together with the expansion
of public data collections, such as ChEMBL and PubChem BioAssay, has made it essential …

Motivation: Identifying protein enzymatic or pharmacological activities are important areas of
research in biology and chemistry. Biological and chemical databases are increasingly …

We have designed and developed a data integration and visualization platform that provides
evidence about the association of known and potential drug targets with diseases. The …