BAMBI integrates biostatistical and artificial intelligence methods to improve RNA biomarker discovery.

ABSTRACT: RNA biomarkers enable early and precise disease diagnosis, monitoring, and prognosis, facilitating personalized medicine and targeted therapeutic strategies. However, identification of RNA biomarkers is hindered by the challenge of analyzing relatively small yet high-dimensional transcriptomics datasets, typically comprising fewer than 1000 biospecimens but encompassing hundreds of thousands of RNAs, especially noncoding RNAs. This complexity leads to several limitations in existing methods, such as poor reproducibility on independent datasets, inability to directly process omics data, and difficulty in identifying noncoding RNAs as biomarkers. Additionally, these methods often yield results that lack biological interpretation and clinical utility. To overcome these challenges, we present

SUBMITTER: Zhou P 

PROVIDER: S-EPMC11929966 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature