ArticleGene expression2010
Quantitative gene expression profiles in real time from expressed sequence tag databases.
Article in Gene expression, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Review
- Specific regions of the brain are capable of fructose metabolism.Brain research · 2017Article
- Efficient Detection of Novel Nuclear Markers for Brassicaceae by Transcriptome Sequencing.PloS one · 2015Article
- Mutations in the promoter region of the aldolase B gene that cause hereditary fructose intolerance.Journal of inherited metabolic disease · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
An accumulation of expressed sequence tag (EST) data in the public domain and the availability of bioinformatic programs have made EST gene expression profiling a common practice. However, the utility and validity of using EST databases (e.g., dbEST) has been criticized, particularly for quantitative assessment of gene expression. Problems with EST sequencing errors, library construction, EST annotation, and multiple paralogs make generation of specific and sensitive qualitative arid quantitative expression profiles a concern. In addition, most EST-derived expression data exists in previously assembled databases. The Virtual Northern Blot (VNB) (http: //tlab.bu.edu/vnb.html) allows generation, evaluation, and optimization of expression profiles in real time, which is especially important for alternatively spliced, novel, or poorly characterized genes. Representative gene families with variable nucleotide sequence identity, tissue specificity, and levels of expression (bcl-xl, aldoA, and cyp2d9) are used to assess the quality of VNB's output. The profiles generated by VNB are more sensitive and specific than those constructed with ESTs listed in preindexed databases at UCSC and NCBI. Moreover, quantitative expression profiles produced by VNB are comparable to quantization obtained from Northern blots and qPCR. The VNB pipeline generates real-time gene expression profiles for single-gene queries that are both qualitatively and quantitatively reliable.
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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.