Deep Learning (DL) has recently enabled unprecedented advances in one of the grand
challenges in computational biology: the half-century-old problem of protein structure …

Deep learning, which is especially formidable in handling big data, has achieved great
success in various fields, including bioinformatics. With the advances of the big data era in …

Nanozymes are nanomaterials that exhibit enzyme‐like biomimicry. In combination with
intrinsic characteristics of nanomaterials, nanozymes have broad applicability in materials …

Understanding the relationship between amino acid sequence and protein function is a long-
standing challenge with far-reaching scientific and translational implications. State-of-the-art …

Subcellular localization of messenger RNAs (mRNAs), as a prevalent mechanism, gives
precise and efficient control for the translation process. There is mounting evidence for the …

Motivation Inferring the properties of a protein from its amino acid sequence is one of the key
problems in bioinformatics. Most state-of-the-art approaches for protein classification are …

In recent years, there has been an increasing interest in exploiting logically specified
background knowledge in order to obtain neural models (i) with a better performance,(ii) …

Hierarchical multi-label classification (HMC) is a challenging classification task extending
standard multi-label classification problems by imposing a hierarchy constraint on the …

Due to the high availability of large-scale annotated image datasets, paramount progress
has been made in deep convolutional neural networks (CNNs) for image classification tasks …

Protein–RNA interactions are of vital importance to a variety of cellular activities. Both
experimental and computational techniques have been developed to study the interactions …