In Silico Transcriptomic Analysis for Identification of Potential Diagnostic and Prognostic Biomarkers and Therapeutic Targets in Cervical Cancer using a Hybrid Genetic Algorithm–Support Vector Machine Approach

The identified gene signatures may serve as candidates for hypothesis generation and provide a computational framework to prioritize biomarkers and therapeutic targets in cervical cancer. However, these findings are based on <i>in silico</i> analyses and require experimental and clinical validation before translation into practice.