ArticleBioinformatics (Oxford, England)2008
Optimal stepwise experimental design for pairwise functional interaction studies.
Article in Bioinformatics (Oxford, England), 2008. 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.
- Article
- Measuring genetic interactions in human cells by RNAi and imaging.Nature protocols · 2014Article
- Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping.Nature methods · 2013Article
- Hierarchical modularity and the evolution of genetic interactomes across species.Molecular cell · 2012Article
- Large-scale genetic epistasis networks using RNAi.Nature methods · 2011Article
- Mapping of signaling networks through synthetic genetic interaction analysis by RNAi.Nature methods · 2011Article
- Genome-wide scoring of positive and negative epistasis through decomposition of quantitative genetic interaction fitness matrices.PloS one · 2010Article
- Missing value imputation for epistatic MAPs.BMC bioinformatics · 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.
Funding
Abstract
motivationPairwise experimental perturbation is increasingly used to probe gene and protein function because these studies offer powerful insight into the activity and regulation of biological systems. Symmetric two-dimensional datasets, such as pairwise genetic interactions are amenable to an optimally designed measurement procedure because of the equivalence of cases and conditions where fewer experimental measurements may be required to extract the underlying structure.
resultsWe show that optimal experimental design can provide improvements in efficiency when collecting data in an iterative manner. We develop a method built on a statistical clustering model for symmetric data and the Fisher information uncertainty estimates, and we also provide simple heuristic approaches that have comparable performance. Using yeast epistatic miniarrays as an example, we show that correct assignment of the major subnetworks could be achieved with <50% of the measurements in the complete dataset. Optimization is likely to become critical as pairwise functional studies extend to more complex mammalian systems where all by all experiments are currently intractable.
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.