ArticleGenome biology2009
Correlating measurements across samples improves accuracy of large-scale expression profile experiments.
Article in Genome biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 20 citations in OpenAlex.
- NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity.Genome biology · 2022Article
- Estimation of Transcription Factor Activity in Knockdown Studies.Scientific reports · 2019Article
- Ubiquitin ligase RNF8 suppresses Notch signaling to regulate mammary development and tumorigenesis.The Journal of clinical investigation · 2018Article
- Quantitative assessment of protein activity in orphan tissues and single cells using the metaVIPER algorithm.Nature communications · 2018Article
- Functional characterization of somatic mutations in cancer using network-based inference of protein activity.Nature genetics · 2016Article
- Identifying candidate drivers of alcohol dependence-induced excessive drinking by assembly and interrogation of brain-specific regulatory networks.Genome biology · 2015Article
- A measure of the signal-to-noise ratio of microarray samples and studies using gene correlations.PloS one · 2012Article
- Biological reprogramming in acquired resistance to endocrine therapy of breast cancer.Oncogene · 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
4 authors at 2 institutions in 1 country.
Funding
Abstract
Gene expression profiling technologies suffer from poor reproducibility across replicate experiments. However, when analyzing large datasets, probe-level expression profile correlation can help identify flawed probes and lead to the construction of truer probe sets with improved reproducibility. We describe methods to eliminate uninformative and flawed probes, account for dependence between probes, and address variability due to transcript-isoform mixtures. We test and validate our approach on Affymetrix microarrays and outline their future adaptation to other technologies.
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.