Advances in Genomic Profiling of Colorectal Cancer Using Nature-Inspired Computing Techniques

Abstract

The mix of cutting-edge sequencing and the ever-progressing computational approach has changed our comprehension of the genomic underpinnings of malignant growth. With the advent of nature-inspired computational techniques, it is easier nowadays to approach the molecular basis of disease pathogenesis. Nature-inspired computational techniques have fueled the progress of genomic investigations into clinical use in patients with cancers, particularly colorectal cancer (CRC). In the genomics landscape, the mutations and epi-mutation increase the risk of CRC and are classified according to dysregulated signaling pathways, aberrant expression, distinct mutational profile of pathogenic genes, copy number alteration, and changes in histone architecture. Furthermore, the advancement in genomic analysis through computational knowledge opens a new gateway to understanding the different drivers that may help predict the clinically relevant biomarker. The expanding significance of nature-inspired computing involves various techniques inspired by different behavioral patterns present in nature that target multiple areas like disease diagnosis, query optimization, clustering, sentiment analysis, etc. In this chapter, we attempt to discuss various integrative approaches that lead to the identification of different nature-inspired computing drivers that may help in the genomic characterization of tumors which may further improve the clinical management of tumors in the future.