BioMark: biomarker analysis tool

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 .

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Publication Details

Journal
BMC Bioinformatics
Published
2026-01-20
DOI
https://doi.org/10.1186/s12859-025-06346-3
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

BioMark: biomarker analysis tool

Ali Cakmak, Cyrille Mesue Njume, Mehmet Ali Balikci
BMC Bioinformatics
Bioinformatics and Genomic Networks
article

BioMark: biomarker analysis tool

Ali Cakmak, Cyrille Mesue Njume, Mehmet Ali Balikci
article en

Abstract

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 .

BMC BioinformaticsVol. 27(1)
TUBITAK BILGEM (TR), Istanbul Technical University (TR)
Industry, innovation and infrastructure
Openalex Percentile: Top 84%
Bioinformatics and Genomic Networks
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