Protein engineering is an emerging field in biotechnology that has the potential to
revolutionize various areas, such as antibody design, drug discovery, food security, ecology …

Despite tremendous efforts in the past two years, our understanding of severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune …

Although deep learning approaches have had tremendous success in image, video and
audio processing, computer vision, and speech recognition, their applications to three …

A suitable feature representation that can both preserve the data intrinsic information and
reduce data complexity and dimensionality is key to the performance of machine learning …

This work introduces a number of algebraic topology approaches, including multi-
component persistent homology, multi-level persistent homology, and electrostatic …

The ability to predict protein–protein interactions is crucial to our understanding of a wide
range of biological activities and functions in the human body, and for guiding drug …

Machine learning techniques will contribution towards making Internet of Things (IoT)
symmetric applications among the most significant sources of new data in the future. In this …

Topological data analysis (TDA) is an emerging mathematical concept for characterizing
shapes in complex data. In TDA, persistence diagrams are widely recognized as a useful …

In the study of dynamical systems on networks or graphs, a key theme is how the network
topology influences stability for steady states or synchronized states. Ideally, one would like …

Protein‐ligand binding is a fundamental biological process that is paramount to many other
biological processes, such as signal transduction, metabolic pathways, enzyme …