ArticleGene regulation and systems biology2009
Microarray data analysis of gene expression evolution.
Article in Gene regulation and systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
- Basic concepts, recent advances, and future perspectives in the diagnosis of bovine mastitis.Journal of veterinary science · 2024Review
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Authors and funding
1 author.
Funding
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Abstract
Microarrays are becoming a widely used tool to study gene expression evolution. A recent paper by Wang and Rekaya describes a comprehensive study of gene expression evolution by microarray. The work provides a perspective to study gene expression evolution in terms of functional enrichment and promoter conservation. It was found that gene expression patterns are highly conserved in some biological processes, but the correlation between promoter and gene expression is insignificant. This scope of this work and future improvement to study gene expression evolution will be discussed in this article.
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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.