ReviewHeart failure reviews2007
The use of transcriptomic biomarkers for personalized medicine.
Review in Heart failure reviews, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed.
- Article
- Structural analysis of genomic and proteomic signatures reveal dynamic expression of intrinsically disordered regions in breast cancer.iScience · 2024Article
- Multi Omics Applications in Biological Systems.Current issues in molecular biology · 2024Review
- Mesenchymal STRO-1/STRO-3Future cardiology · 2023Review
- Transcriptomics, metabolomics, and in-silico drug predictions for liver damage in young and aged burn victims.Communications biology · 2023Article
- Toxicology, Nanotoxicology and Occupational Diseases Related to Chemical Exposure.International journal of molecular sciences · 2022Article
- Identification of hub genes and molecular pathways in human T-lymphotropic virus type 1 associated diseases using protein-protein interactions networks.Iranian journal of microbiology · 2022Article
- Exposure of Toluene Diisocyanate Induces DUSP6 and p53 through Activation of TRPA1 Receptor.International journal of molecular sciences · 2022Article
- At-home blood collection and stabilization in high temperature climates usingFrontiers in digital health · 2022Article
- A Pilot Study of Gene Expression Analysis in Peripheral Blood Mononuclear Cells in Response to a Hypocaloric Mediterranean Diet.Disease markers · 2022Article
- Integration of Epigenetic Mechanisms into Non-Genotoxic Carcinogenicity Hazard Assessment: Focus on DNA Methylation and Histone Modifications.International journal of molecular sciences · 2021Review
- Integrated Gene Expression Profiling Analysis Reveals Potential Molecular Mechanisms and Candidate Biomarkers for Early Risk Stratification and Prediction of STEMI and Post-STEMI Heart Failure Patients.Frontiers in cardiovascular medicine · 2021Article
- Identification of time‑series differentially expressed genes and pathways associated with heart failure post‑myocardial infarction using integrated bioinformatics analysis.Molecular medicine reports · 2019Article
- Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysis.Biomedical engineering online · 2019Article
- Comparison of statistical methods and the use of quality control samples for batch effect correction in human transcriptome data.PloS one · 2018Article
- Transcriptomic Analysis Identifies the Effect of Beta-Blocking Agents on a Molecular Pathway of Contraction in the Heart and Predicts Response to Therapy.JACC. Basic to translational science · 2016Review
- Highly informative marker sets consisting of genes with low individual degree of differential expression.Scientific reports · 2015Article
- Gene expression profiling reveals potential prognostic biomarkers associated with the progression of heart failure.Genome medicine · 2015Article
- Estimation of treatment policies based on functional predictors.Statistica Sinica · 2014Article
- Big data: the next frontier for innovation in therapeutics and healthcare.Expert review of clinical pharmacology · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microarrays are a high throughput technology that allows the quantification of tens of thousands of RNA transcripts in a single reaction. This new technology offers the promise of comprehensive study of disease at a genomic level, potentially identifying novel molecular abnormalities, developing novel clinical biomarkers, and investigating drug efficacy. The ability to develop a molecular profile corresponding to a therapeutic effect is the basis for the concept of drug repositioning. With regard to prediction of clinical events, microarray technology has the potential to contribute to the development of sophisticated new biomarkers useful as predictors of disease etiology, outcome, and responsiveness to therapy-so-called personalized medicine. Currently progress in the field is hampered by a degree of skepticism about the reliability of microarray data and its relevance for clinical applications. Here we discuss possible pitfalls of transcriptomic analysis, review current developments in the cardiovascular area and address the use of transcriptomics for clinical applications.
Indexed as
Identifiers
17393305What 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.