A Boolean System for Breast Cancer Detection Using MicroRNA-Based Logic Gates

MicroRNAs (miRNAs) have become valuable biomarkers for early cancer detection. Studies highlight their high sensitivity and specificity in identifying early cancer-related changes. Researchers have explored miRNAs' diagnostic potential by developing various techniques, including DNA-based logic gates designed to detect disease-specific miRNAs. However, the logical relationships between miRNAs and their role in disease progression remain unexplored in existing research. This paper introduces a Boolean system that utilises miRNA data as inputs to identify a logical function involving seven miRNAs linked to breast cancer. The proposed Boolean function achieves an accuracy of 97.03% in breast cancer diagnosis. These findings can be incorporated into R software for bioinformatics analysis and adapted for diagnosing other diseases by adjusting the input miRNAs. This approach shows potential for advancements in DNA computing, biomedical research, and clinical diagnostics.