Flexynesis: A deep learning toolkit for bulk multi-omics data integration for precision oncology and beyond.

ABSTRACT: Accurate decision making in precision oncology depends on integration of multimodal molecular information, for which various deep learning methods have been developed. However, most deep learning-based bulk multi-omics integration methods lack transparency, modularity, deployability, and are limited to narrow tasks. To address these limitations, we introduce Flexynesis, which streamlines data processing, feature selection, hyperparameter tuning, and marker discovery. Users can choose from deep learning architectures or classical supervised machine learning methods with a standardized input interface for single/multi-task training and evaluation for regression, classification, and survival modeling. We showcase the tool's capability across diverse use-cases in precision oncology. To maximiz

SUBMITTER: Uyar B 

PROVIDER: S-EPMC12432156 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature