Abstract Protein Structure Prediction is a central topic in Structural Bioinformatics. Since
the'60s statistical methods, followed by increasingly complex Machine Learning and recently …

Motivation The accuracy of predicting protein local and global structural properties such as
secondary structure and solvent accessible surface area has been stagnant for many years …

Direct prediction of protein structure from sequence is a challenging problem. An effective
approach is to break it up into independent sub-problems. These sub-problems such as …

This paper aims to provide a comprehensive review of the trends and challenges of deep
neural networks for protein secondary structure prediction (PSSP). In recent years, deep …

Accurate prediction of protein secondary structure is essential for accurate sequence
alignment, three‐dimensional structure modeling, and function prediction. The accuracy of …

Because a nearly constant distance between two neighbouring Cα atoms, local backbone
structure of proteins can be represented accurately by the angle between Cαi− 1 Cαi …

Suitable for advanced undergraduates and postgraduates, Understanding Bioinformatics
provides a definitive guide to this vibrant and evolving discipline. The book takes a …

We present an approach to assess antibody CDR-H3 loops according to their dynamic
properties using molecular dynamics simulations. We selected six antibodies in three pairs …

An integrated system of neural networks, called SPINE, is established and optimized for
predicting structural properties of proteins. SPINE is applied to three‐state secondary …

Aerial insects can nimbly navigate in cluttered natural environments while they interact with
delicate objects such as flowers and leaves. To achieve insect-like agility and robustness …