Motivation Machine learning (ML) methods are motivated by the need to automate
information extraction from large datasets in order to support human users in data-driven …

Simple Summary The rapidly advancing field of deep learning, specifically transformer-
based architectures and attention mechanisms, has found substantial applicability in …

Motivation Proteins play crucial roles in biological processes, with their functions being
closely tied to thermodynamic stability. However, measuring stability changes upon point …

Glioblastoma multiforme (GBM) is the most common type of brain tumors with high
recurrence and mortality rates. After chemotherapy treatment, GBM patients still show a high …

Motivation Discovering the drug–target interactions (DTIs) is a crucial step in drug
development such as the identification of drug side effects and drug repositioning. Since …

Survival analysis is critical to cancer prognosis estimation. High-throughput technologies
facilitate the increase in the dimension of genic features, but the number of clinical samples …

Background Homologous recombination is a robust, broadly error-free mechanism of double-
strand break repair, and deficiencies lead to PARP inhibitor sensitivity. Patients displaying …

Graph neural network (GNN) is a formidable deep learning framework that enables the
analysis and modeling of intricate relationships present in data structured as graphs. In …

The innovation of high‐throughput technologies and medical radiomics allows biomedical
data to accumulate at an astonishing rate. Several promising deep learning (DL) methods …

Advancing the domain of biomedical investigation, integrated multi-omics data have shown
exceptional performance in elucidating complex human diseases. However, as the variety of …