<p>Cancer is a complex and multifaceted disease that arises when cells begin to grow and divide uncontrollably, ultimately disrupting normal physiological functions and potentially leading to death. Various factors cause it and can metastasize, survive in any environment, and develop resistance to therapy. In healthy organisms, cells rely on metabolism, the conversion of nutrients into energy and essential biomolecules to support growth, repair, and normal cellular functions. However, cancer cells reprogram their metabolic pathways to meet the increased demands of rapid proliferation and survival. Metabolomics is the branch of science that studies small metabolites and is emerging as one of the major fields that will provide insight into cancer research, thereby providing information about alterations in metabolic pathways that have aided cancer growth. In recent years, numerous computational tools have been developed to aid the study of cancer. Multiple databases have been built to store and retrieve metabolomics data to support cancer studies. In parallel, a wide range of computational tools and packages have been created to process high-throughput data, identify altered metabolites, and map metabolic pathways. These advancements have provided insight into cancer biology and the metabolomic alterations that lead to cancer proliferation. Moreover, they have facilitated the discovery of potential biomarkers and therapeutic targets, enabling the identification of disease mechanisms and effective treatment strategies. Therefore, this study aims to explore the role of metabolomics in cancer research, highlight metabolomics resources, and examine computational insights and their role in advancing cancer research.</p>