Motivation Proteins are ubiquitous molecules whose function in biological processes is
determined by their 3D structure. Experimental identification of a protein's structure can be …

Motivation Quality assessment (QA) of predicted protein tertiary structure models plays an
important role in ranking and using them. With the recent development of deep learning end …

Motivation Protein model quality assessment (QA) is a crucial and yet open problem in
structural bioinformatics. The current best methods for single-model QA typically combine …

Blind estimation of local (per-residue) and global (for the whole structure) accuracies in
protein structure models is an essential step in many protein modeling applications. With the …

Background Protein quality assessment (QA) useful for ranking and selecting protein models
has long been viewed as one of the major challenges for protein tertiary structure prediction …

Motivation Protein model quality assessment is a key component of protein structure
prediction. In recent research, the voxelization feature was used to characterize the local …

While DeepMind has tentatively solved protein folding, its inverse problem--protein design
which predicts protein sequences from their 3D structures--still faces significant challenges …

Motivation Methods that estimate the quality of a 3D protein structure model in absence of an
experimental reference structure are crucial to determine a model's utility and potential …

Protein model quality assessment plays an important role in protein structure prediction,
protein design and drug discovery. In this work, DeepUMQA2, a substantially improved …

Motivation Automated function prediction (AFP) of proteins is a large-scale multi-label
classification problem. Two limitations of most network-based methods for AFP are (i) a …