ReviewInternational journal of data mining and bioinformatics2010
Matrix factorisation methods applied in microarray data analysis.
Review in International journal of data mining and bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed, 36 citations in OpenAlex.
- Effect of common medications on the expression of SARS-CoV-2 entry receptors in liver tissue.Archives of toxicology · 2020Article
- Iterative sub-network component analysis enables reconstruction of large scale genetic networks.BMC bioinformatics · 2015Article
- biDCG: a new method for discovering global features of DNA microarray data via an iterative re-clustering procedure.PloS one · 2014Article
- Identifying context-specific transcription factor targets from prior knowledge and gene expression data.IEEE transactions on nanobioscience · 2013Article
- Matrix Factorization for Transcriptional Regulatory Network Inference.IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology proceedings. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology · 2012Article
- Matrix factorization for recovery of biological processes from microarray data.Methods in enzymology · 2009Article
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 at 2 institutions in 1 country.
Funding
Abstract
Numerous methods have been applied to microarray data to group genes into clusters that show similar expression patterns. These methods assign each gene to a single group, which does not reflect the widely held view among biologists that most, if not all, genes in eukaryotes are involved in multiple biological processes and therefore will be multiply regulated. Here, we review several methods of matrix factorisation that identify patterns of behaviour in transcriptional response and assign genes to multiple patterns. We focus on these methods rather than traditional clustering methods applied to microarray data, which assign one gene to one cluster.
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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.