Motivation Disease gene prioritization consists in identifying genes that are likely to be
involved in the mechanisms of a given disease, providing a ranking of such genes. Recently …

Automated protein function prediction is a crucial and widely studied problem in
bioinformatics. Computationally, protein function is a multilabel classification problem where …

Introduction: Connections among neurons form one of the most amazing and effective
network in nature. At higher level, also the functional structures of the brain is organized as a …

Positive and unlabeled learning (PU learning) is a significant binary classification task in
machine learning; it focuses on training accurate classifiers using positive data and …

Disease gene identification using computational methods is one of the most challenging
issues to improve the treatment and diagnosis of Parkinson's disease (PD). Various …

By deepening our understanding of the relationship between microorganisms and disease,
we can study the formation and pathogenesis of various complex diseases. This, in turn …

Deep learning has been extensively utilized in the domains of bioinformatics and
chemoinformatics, yielding compelling results. However, neural networks have …