ArticleFrontiers in genetics2013
The systems genetics resource: a web application to mine global data for complex disease traits.
Article in Frontiers in genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
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Who cites it
10 citing papers in PubMed.
- RIPK1 gene variants associate with obesity in humans and can be therapeutically silenced to reduce obesity in mice.Nature metabolism · 2020Article
- A GWAS approach identifies Dapp1 as a determinant of air pollution-induced airway hyperreactivity.PLoS genetics · 2019Article
- Functional Characterization of theCirculation · 2017Article
- Propelling the paradigm shift from reductionism to systems nutrition.Genes & nutrition · 2017Article
- Genetic Dissection of Cardiac Remodeling in an Isoproterenol-Induced Heart Failure Mouse Model.PLoS genetics · 2016Article
- The Hybrid Mouse Diversity Panel: a resource for systems genetics analyses of metabolic and cardiovascular traits.Journal of lipid research · 2016Review
- Genetic network identifies novel pathways contributing to atherosclerosis susceptibility in the innominate artery.BMC medical genomics · 2014Article
- [Genetic analyses as basis for a personalized medicine in patients with coronary artery disease].Herz · 2014Article
- Mouse phenome database.Nucleic acids research · 2014Article
- Systems genetics approaches to understand complex traits.Nature reviews. Genetics · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The Systems Genetics Resource (SGR) (http://systems.genetics.ucla.edu) is a new open-access web application and database that contains genotypes and clinical and intermediate phenotypes from both human and mouse studies. The mouse data include studies using crosses between specific inbred strains and studies using the Hybrid Mouse Diversity Panel. SGR is designed to assist researchers studying genes and pathways contributing to complex disease traits, including obesity, diabetes, atherosclerosis, heart failure, osteoporosis, and lipoprotein metabolism. Over the next few years, we hope to add data relevant to deafness, addiction, hepatic steatosis, toxin responses, and vascular injury. The intermediate phenotypes include expression array data for a variety of tissues and cultured cells, metabolite levels, and protein levels. Pre-computed tables of genetic loci controlling intermediate and clinical phenotypes, as well as phenotype correlations, are accessed via a user-friendly web interface. The web site includes detailed protocols for all of the studies. Data from published studies are freely available; unpublished studies have restricted access during their embargo period.
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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 Socratic graph.