Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …

Learning on 3D structures of large biomolecules is emerging as a distinct area in machine
learning, but there has yet to emerge a unifying network architecture that simultaneously …

There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …

Motivation Proteases are enzymes that cleave target substrate proteins by catalyzing the
hydrolysis of peptide bonds between specific amino acids. While the functional proteolysis …

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 …

Methods to reliably estimate the accuracy of 3D models of proteins are both a fundamental
part of most protein folding pipelines and important for reliable identification of the best …

Protein structures play a very important role in biomedical research, especially in drug
discovery and design, which require accurate protein structures in advance. However …

Motivation Residue contact prediction was revolutionized recently by the introduction of
direct coupling analysis (DCA). Further improvements, in particular for small families, have …

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 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 …