Conventional wet laboratory testing, validations, and synthetic procedures are costly and
time-consuming for drug discovery. Advancements in artificial intelligence (AI) techniques …

Introduction Intrinsic disorder prediction field develops, assesses, and deploys
computational predictors of disorder in protein sequences and constructs and disseminates …

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of
biological macromolecular complexes. Picking single-protein particles from cryo-EM …

Neoantigens recognized by cytotoxic T cells are effective targets for tumor-specific immune
responses for personalized cancer immunotherapy. Quite a few neoantigen identification …

Phosphorylation is one of the most important post-translational modifications and plays a
pivotal role in various cellular processes. Although there exist several computational tools to …

Loops are key components of protein structures, involved in many biological functions. Due
to their conformational variability, the structural investigation of loops is a difficult topic …

Accurate protein structure prediction using computational methods remains a challenge in
molecular biology. Recent advances in AI-powered algorithms provide a transformative …

Following the hugely successful application of deep learning methods to protein structure
prediction, an increasing number of design methods seek to leverage generative models to …

With climate emergency, COVID-19, and the rise of planetary health scholarship, the binary
of human and ecosystem health has been deeply challenged. The interdependence of …

Protein subcellular localization prediction is of great significance in bioinformatics and
biological research. Most of the proteins do not have experimentally determined localization …