ArticleBMC proceedings2007
Pattern-based mining strategy to detect multi-locus association and gene x environment interaction.
Article in BMC proceedings, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Detecting gene-gene interactions for complex quantitative traits using generalized fuzzy classification.BMC bioinformatics · 2018Article
- Analyzing Interaction of μ-, δ- and κ-opioid Receptor Gene Variants on Alcohol or Drug Dependence Using a Pattern Discovery-based Method.Journal of addiction research & therapy · 2013Article
- Identifying interacting genetic variations by fish-swarm logic regression.BioMed research international · 2013Article
- Prioritizing GWAS results: A review of statistical methods and recommendations for their application.American journal of human genetics · 2010Review
- Detecting gene-gene interactions that underlie human diseases.Nature reviews. Genetics · 2009Review
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
As genome-wide association studies grow in popularity for the identification of genetic factors for common and rare diseases, analytical methods to comb through large numbers of genetic variants efficiently to identify disease association are increasingly in demand. We have developed a pattern-based data-mining approach to discover unlinked multilocus genetic effects for complex disease and to detect genotype x phenotype/genotype x environment interactions. On a densely mapped chromosome 18 data set for rheumatoid arthritis that was made available by Genetic Analysis Workshop 15, this method detected two potential two-locus associations as well as a putative two-locus gene x gender interaction.
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.