Solvent accessible surface area (SASA) of proteins has always been considered as a
decisive factor in protein folding and stability studies. It is defined as the surface …

Protein fold recognition is critical for studying the structures and functions of proteins. The
existing protein fold recognition approaches failed to efficiently calculate the pairwise …

Protein sequence comparison methods have grown increasingly sensitive during the last
decade and can often identify distantly related proteins sharing a common ancestor some 3 …

Motivation: In recent years, development of a single-method fold-recognition server lags
behind consensus and multiple template techniques. However, a good consensus …

Protein mutations can lead to structural changes that affect protein function and result in
disease occurrence. In protein engineering, drug design or and optimization industries …

Protein fold recognition is one of the most critical tasks to explore the structures and
functions of the proteins based on their primary sequence information. The existing protein …

For accurate recognition of protein folds, a deep learning network method (DN-Fold) was
developed to predict if a given query-template protein pair belongs to the same structural …

As a key for studying the protein structures, protein fold recognition is playing an important
role in predicting the protein structures associated with COVID-19 and other important …

As one of the most important tasks in protein structure prediction, protein fold recognition has
attracted more and more attention. In this regard, some computational predictors have been …

As an important task in protein structure and function studies, protein fold recognition has
attracted more and more attention. The existing computational predictors in this field treat …