AI-Assisted Literature Mining Framework for miRNA–Target Mapping in Colorectal Cancer

Colorectal cancer is an important cause of mortality worldwide, and the complex molecular mechanisms that govern the development, progression, and spread of the disease are complex. Among these complex mechanisms, the role of miRNAs in the regulation of gene expression at the post-transcriptional level through the modulation of the expression of multiple target genes that are integral parts of oncogenic pathways is crucial. The discovery of the interactions between miRNAs and their targets is therefore essential in the understanding of colorectal cancer and the discovery of potential biomarkers and therapeutic targets. The exponential growth of scientific literature in the field of biomedicine has made the discovery of such interactions from the scientific literature an inefficient and difficult task. To overcome the inefficiencies associated with the traditional approaches for the discovery of miRNA–target interactions, the present study proposes a conceptual framework for AI-assisted literature mining for the discovery of miRNA–target interactions that are crucial in the understanding of colorectal cancer. The framework for the discovery of miRNA–target interactions is structured and aims at synthesizing the scientific evidence that is disseminated in the scientific community. The framework is therefore crucial in the development of the field of bioinformatics.