Research Information System
in: Big Data Analytics in Biostatistics and Bioinformatics, Yichuan Zhao,Ding-Geng Chen, Editor, Springer Nature Switzerland Ag, Zug, pp.123-145, 2026
High-throughput technologies have recently attracted much attention in academia. These technologies enable gathering information from various biological datasets, including genomics, transcriptomics, proteomics, and metabolomics data. Integrating and analyzing various datasets will allow us to accurately diagnose the disease, deepen our understanding of biological processes, and develop advanced treatment approaches. Numerous integration techniques have been developed for this aim, enabling researchers to unravel the complex patterns and underlying mechanisms behind biological occurrences, including those associated with illnesses. This study aims to explore and employ various data integration methodologies and machine-learning techniques on multi-omics data to predict disease classes using real datasets.