Although remarkable advances have been reported in high-throughput sequencing, the
ability to aptly analyze a substantial amount of rapidly generated biological …

Medical discoveries mainly depend on the capability to process and analyze biological
datasets, which inundate the scientific community and are still expanding as the cost of next …

Possible drug–food constituent interactions (DFIs) could change the intended efficiency of
particular therapeutics in medical practice. The increasing number of multiple-drug …

Accurate prediction of immunogenic peptide recognized by T cell receptor (TCR) can greatly
benefit vaccine development and cancer immunotherapy. However, identifying …

Abstract Analysis and prediction of drug-target interactions (DTIs) play an important role in
understanding drug mechanisms, as well as drug repositioning and design. Machine …

Early identification of degenerative processes in the human brain is considered essential for
providing proper care and treatment. This may involve detecting structural and functional …

A novel coronavirus (COVID-19), which has become a great concern for the world, was
identified first in Wuhan city in China. The rapid spread throughout the world was …

In this paper, a computational framework is proposed that merges mechanistic modeling
with deep neural networks obeying the Systems Biology Markup Language (SBML) …

Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the
modern drug discovery pipeline as it mitigates the cost, time, and resources required to …

Accurately identifying protein–ATP binding residues is important for protein function
annotation and drug design. Previous studies have used classic machine-learning …