ArticleBMC bioinformatics2026
BioMark: biomarker analysis tool.
Article in BMC bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Artificial intelligence in biomarker discovery for diseases: diagnostic and therapeutic prospects.Signal transduction and targeted therapy · 2026Review
- When complexity does not pay: benchmarking deep learning and ensemble methods for biomarker discovery.Briefings in bioinformatics · 2026Article
- UBA6 serves as a prognostic biomarker and promotes tumor progression in pancreatic ductal adenocarcinoma.Translational cancer research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
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 .
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.