Discovery and development of biopeptides are time‐consuming, laborious, and dependent
on various factors. Data‐driven computational methods, especially machine learning (ML) …

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 …

Computational methods that operate on three-dimensional molecular structure have the
potential to solve important questions in biology and chemistry. In particular, deep neural …

Protein function prediction is a major challenge in the field of bioinformatics which aims at
predicting the functions performed by a known protein. Many protein data forms like protein …

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 …

Cybersecurity has become an emerging challenge for business information management in
recent years. Artificial Intelligence (AI) is widely used in different field, but it is still relatively …

Neuropeptides acting as signaling molecules in the nervous system of various animals play
crucial roles in a wide range of physiological functions and hormone regulation behaviors …

After the development of next-generation sequencing techniques, protein sequences are
abundantly available. Determining the functional characteristics of these proteins is costly …

Introduction Peptidomics is an emerging field of omics sciences using advanced isolation,
analysis, and computational techniques that enable qualitative and quantitative analyses of …

Motivation Protein model quality assessment (QA) is an essential component in protein
structure prediction, which aims to estimate the quality of a structure model and/or select the …