Non-coding regions of the genome are critical in gene regulation, particularly in reaction to environmental stress. Advances in genomic technology have made it possible to identify and characterise stress-responsive non-coding elements such as long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and enhancer RNAs (eRNAs), all of which regulate gene expression under stress. This chapter gives details about genetic resources and bioinformatic methods available for studying these regulatory areas, shedding light on their functional significance. Public archives like Ensembl, NONCODE, and RNAcentral provide large datasets for non-coding RNA annotation, while computational tools like RNA fold, Target Scan, and IncRNA SNP aid in predictive analysis and functional validation. Furthermore, multi-omics integration, which includes transcriptomics, epigenomics, and proteomics, helps us comprehend stress adaptation processes. Despite advances, issues like insufficient annotation, tissue-specific expression variability, and data integration problems persist. This chapter also highlights current techniques, such as artificial intelligence-driven ncRNA prediction and CRISPR-based functional validation, which shows promise for furthering stress biology research. Understanding stress-responsive non-coding regions reveals important information about plant and animal stress adaptation, with potential implications in agriculture, medicine, and biotechnology. Researchers can better understand the complex regulatory networks that govern stress resilience by leveraging genomic resources and computational breakthroughs.