ArticleBMC bioinformatics2009
ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 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
43 citing papers in PubMed.
- DNA Molecular Computing with Weighted Signal Amplification for Cancer miRNA Biomarker Diagnostics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Multi-dimensional characterization of cellular states reveals clinically relevant immunological subtypes and therapeutic vulnerabilities in ovarian cancer.Journal of translational medicine · 2025Article
- Article
- LC3A-mediated autophagy regulates lung cancer cell plasticity.Autophagy · 2022Article
- Unsupervised Algorithms for Microarray Sample Stratification.Methods in molecular biology (Clifton, N.J.) · 2022Article
- COMSUC: A web server for the identification of consensus molecular subtypes of cancer based on multiple methods and multi-omics data.PLoS computational biology · 2021Article
- HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets.PloS one · 2021Article
- 'Multi-omic' data analysis using O-miner.Briefings in bioinformatics · 2019Article
- Efficacy of Integrating a Novel 16-Gene Biomarker Panel and Intelligence Classifiers for Differential Diagnosis of Rheumatoid Arthritis and Osteoarthritis.Journal of clinical medicine · 2019Article
- Low-dose aspirin protective effects are correlated with deregulation of HNF factor expression in the preeclamptic placentas from mice and humans.Cell death discovery · 2019Article
- Computational systems biology approaches for Parkinson's disease.Cell and tissue research · 2018Review
- Cancer reversion with oocyte extracts is mediated by cell cycle arrest and induction of tumour dormancy.Oncotarget · 2018Article
- Antibody Profiling of Kawasaki Disease UsingMolecular & cellular proteomics : MCP · 2018Article
- Article
- Id2 Collaborates with Id3 To Suppress Invariant NKT and Innate-like Tumors.Journal of immunology (Baltimore, Md. : 1950) · 2017Article
- Discriminative identification of transcriptional responses of promoters and enhancers after stimulus.Nucleic acids research · 2017Article
- A feature selection method based on multiple kernel learning with expression profiles of different types.BioData mining · 2017Article
- Construction and evaluation of yeast expression networks by database-guided predictions.Microbial cell (Graz, Austria) · 2016Article
- KIAA0101 is associated with human renal cell carcinoma proliferation and migration induced by erythropoietin.Oncotarget · 2016Article
- Transcriptome-wide functional characterization reveals novel relationships among differentially expressed transcripts in developing soybean embryos.BMC genomics · 2015Article
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
backgroundStatistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks.
resultsWe present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining.
conclusionArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.
Indexed as
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.