ArticleBMC bioinformatics2010
Hybridization thermodynamics of NimbleGen microarrays.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Should all smokers use combination smoking cessation pharmacotherapy? Using novel analytic methods to detect differential treatment effects over 8 weeks of pharmacotherapy.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2012Trial
- Review
- Alternating EM algorithm for a bilinear model in isoform quantification from RNA-seq data.Bioinformatics (Oxford, England) · 2020Article
- Experiences with workflows for automating data-intensive bioinformatics.Biology direct · 2015Article
- A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium.Nature biotechnology · 2014Article
- A revised design for microarray experiments to account for experimental noise and uncertainty of probe response.PloS one · 2014Article
- Physico-chemical foundations underpinning microarray and next-generation sequencing experiments.Nucleic acids research · 2013Review
- Intra-platform comparison of 25-mer and 60-mer oligonucleotide Nimblegen DNA microarrays.BMC research notes · 2013Article
- Article
- The impact of quantitative optimization of hybridization conditions on gene expression analysis.BMC bioinformatics · 2011Article
- Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development.BMC bioinformatics · 2010Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWhile microarrays are the predominant method for gene expression profiling, probe signal variation is still an area of active research. Probe signal is sequence dependent and affected by probe-target binding strength and the competing formation of probe-probe dimers and secondary structures in probes and targets.
resultsWe demonstrate the benefits of an improved model for microarray hybridization and assess the relative contributions of the probe-target binding strength and the different competing structures. Remarkably, specific and unspecific hybridization were apparently driven by different energetic contributions: For unspecific hybridization, the melting temperature Tm was the best predictor of signal variation. For specific hybridization, however, the effective interaction energy that fully considered competing structures was twice as powerful a predictor of probe signal variation. We show that this was largely due to the effects of secondary structures in the probe and target molecules. The predictive power of the strength of these intramolecular structures was already comparable to that of the melting temperature or the free energy of the probe-target duplex.
conclusionsThis analysis illustrates the importance of considering both the effects of probe-target binding strength and the different competing structures. For specific hybridization, the secondary structures of probe and target molecules turn out to be at least as important as the probe-target binding strength for an understanding of the observed microarray signal intensities. Besides their relevance for the design of new arrays, our results demonstrate the value of improving thermodynamic models for the read-out and interpretation of microarray signals.
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