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Biomarkers play a pivotal role in disease diagnosis and prognosis by offering molecular insights into biological states. The rapid growth of high-throughput omics technologies has enabled the generation of large-scale biomarker datasets, yet analyzing these complex, high-dimensional data remains a major challenge-particularly for researchers lacking advanced computational expertise. While numerous tools exist for omics data analysis, many fall short in providing an integrated, user-friendly environment tailored specifically for biomarker discovery and interpretation. To address this gap, we present BioMark, a web-based platform designed to streamline biomarker analysis across diverse omics types. BioMark integrates robust statistical methods with widely used machine learning algorithms to support key workflows including statistical analysis, dimensionality reduction, classification, and subsequent model explanation. The platform emphasizes accessibility, offering intuitive visualizations and automated reporting to facilitate interpretation and dissemination of results. Notably, BioMark also offers a feature-ranking strategy that consolidates outputs from multiple analytical methods, enhancing the robustness of biomarker identification. By lowering the barrier to advanced biomarker analytics, BioMark empowers a broader range of researchers to uncover clinically relevant molecular signatures and accelerate translational research. Biomark is available online at https://bioinf.itu.edu.tr/biomark .
Balikci et al. (2026) studied this question.