Recent advance in large-scale genome se-quencing has generated a huge volume of pro-
tein sequences. In order to timely utilize the in-formation hidden in these newly discovered …

When a protein's function cannot be experimentally determined, it can often be inferred from
sequence similarity. Should this process fail, analysis of the protein structure can provide …

Structural and physiochemical descriptors extracted from sequence data have been widely
used to represent sequences and predict structural, functional, expression and interaction …

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

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 …

Motivation Annotation of enzyme function has a broad range of applications, such as
metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused …

Motivation: Computational approaches to protein function prediction infer protein function by
finding proteins with similar sequence, structure, surface clefts, chemical properties, amino …

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 …

With the rapid increment of protein sequence data, it is indispensable to develop automated
and reliable predictive methods for protein function annotation. One approach for facilitating …