On Finding Non Coding Elements in Genome: A Machine Intelligence Approach

The human genome’s exploration has uncovered a vast realm of genetic elements, extending beyond traditional coding regions. Recent studies emphasize non-coding elements’ crucial roles in gene regulation and cellular processes. This paper introduces a novel approach, utilizing machine intelligence techniques, to identify and characterize these elements. Our method involves comparing healthy and unhealthy human genomes to detect genetic alterations linked to health conditions. Leveraging advanced data structure algorithms, we efficiently process vast genomic datasets, pinpointing potential non-coding elements with disease relevance. Through extensive validation, our approach consistently reveals regions of regulatory importance, shedding light on disease mechanisms. Integrating machine intelligence with genomics advances our understanding of non-coding elements and their role in human health.