ArticleJournal of clinical bioinformatics2011
Bioinformatic-driven search for metabolic biomarkers in disease.
Article in Journal of clinical bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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
29 citing papers in PubMed, 84 citations in OpenAlex.
- Evaluation of SLOG/TCI-III pediatric system on target control infusion of propofol.Journal of translational medicine · 2011Trial
- Inflammasomes in respiratory diseases: from disease pathogenesis to drug development and use of multi-omics.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- Bioinformatics-led identification of pathophysiological hallmark genes in diabesotension via graph clustering method.Journal of diabetes and metabolic disorders · 2025Article
- Implications of ZNF334 gene in lymph node metastasis of lung SCC: potential bypassing of cellular senescence.Journal of translational medicine · 2024Article
- Identification of CXCL16 as a diagnostic biomarker for obesity and intervertebral disc degeneration based on machine learning.Scientific reports · 2023Article
- Article
- Article
- Degree Adjusted Large-Scale Network Analysis Reveals Novel Putative Metabolic Disease Genes.Biology · 2021Article
- Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine.International journal of molecular sciences · 2021Review
- Robust clinical marker identification for diabetic kidney disease with ensemble feature selection.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Advances in the design of nanomaterial-based electrochemical affinity and enzymatic biosensors for metabolic biomarkers: A review.Mikrochimica acta · 2018Review
- A novel network-based approach for discovering dynamic metabolic biomarkers in cardiovascular disease.PloS one · 2018Article
- Feature Selection Methods for Early Predictive Biomarker Discovery Using Untargeted Metabolomic Data.Frontiers in molecular biosciences · 2016Article
- Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity.PLoS computational biology · 2015Article
- Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers.Journal of cellular and molecular medicine · 2015Review
- Two of Them Do It Better: Novel Serum Biomarkers Improve Autoimmune Hepatitis Diagnosis.PloS one · 2015Article
- Soluble biomarkers development in osteoarthritis: from discovery to personalized medicine.Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals · 2015Review
- Application of oncoproteomics to aberrant signalling networks in changing the treatment paradigm in acute lymphoblastic leukaemia.Journal of cellular and molecular medicine · 2015Article
- Specific metabolic biomarkers as risk and prognostic factors in colorectal cancer.World journal of gastroenterology · 2014Review
- Multi-TGDR, a multi-class regularization method, identifies the metabolic profiles of hepatocellular carcinoma and cirrhosis infected with hepatitis B or hepatitis C virus.BMC bioinformatics · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The search and validation of novel disease biomarkers requires the complementary power of professional study planning and execution, modern profiling technologies and related bioinformatics tools for data analysis and interpretation. Biomarkers have considerable impact on the care of patients and are urgently needed for advancing diagnostics, prognostics and treatment of disease. This survey article highlights emerging bioinformatics methods for biomarker discovery in clinical metabolomics, focusing on the problem of data preprocessing and consolidation, the data-driven search, verification, prioritization and biological interpretation of putative metabolic candidate biomarkers in disease. In particular, data mining tools suitable for the application to omic data gathered from most frequently-used type of experimental designs, such as case-control or longitudinal biomarker cohort studies, are reviewed and case examples of selected discovery steps are delineated in more detail. This review demonstrates that clinical bioinformatics has evolved into an essential element of biomarker discovery, translating new innovations and successes in profiling technologies and bioinformatics to clinical application.
Identifiers
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.