Modern drug discovery is primarily based on the search and subsequent testing of drug
candidates acting on a preselected therapeutic target. Progress in genomics, protein …

Sequence-based analysis and prediction are fundamental bioinformatic tasks that facilitate
understanding of the sequence (-structure)-function paradigm for DNAs, RNAs and proteins …

Background: Calculation of ligand-binding affinity is an open problem in computational
medicinal chemistry. The ability to computationally predict affinities has a beneficial impact …

With the explosive growth of biological sequences generated in the post-genomic era, one
of the most challenging problems in bioinformatics and computational biology is to …

Nuclear receptors are key transcription factors that regulate crucial gene networks
responsible for cell growth, differentiation, and homeostasis. Nuclear receptors form a …

Sequence-derived structural and physicochemical features have frequently been used in the
development of statistical learning models for predicting proteins and peptides of different …

Motivation: MicroRNAs (miRNAs) are small ncRNAs participating in diverse cellular and
physiological processes through the post-transcriptional gene regulatory pathway. Critically …

Anticancer peptides (ACPs), a series of short bioactive peptides, are promising candidates
in fighting against cancer due to their high activity, low toxicity, and not likely cause drug …

Knowledge of protein function is important for biological, medical and therapeutic studies,
but many proteins are still unknown in function. There is a need for more improved functional …

Motivation Detection of RNA-binding proteins (RBPs) is essential since the RNA-binding
proteins play critical roles in post-transcriptional regulation and have diverse roles in various …