ArticleBioinformatics (Oxford, England)2014
Causal analysis approaches in Ingenuity Pathway Analysis.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04088630 (Fingolimod as a Treatment of Cerebral Edema After Intracerebral Hemorrhage), which is not on this map. Cited by 3,949 papers.
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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.
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Fingolimod as a Treatment of Cerebral Edema After Intracerebral Hemorrhage
Who cites it
3,949 citing papers in PubMed.
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4 authors.
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Abstract
motivationPrior biological knowledge greatly facilitates the meaningful interpretation of gene-expression data. Causal networks constructed from individual relationships curated from the literature are particularly suited for this task, since they create mechanistic hypotheses that explain the expression changes observed in datasets.
resultsWe present and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene-expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base. We extend the method to predict downstream effects on biological functions and diseases and demonstrate the validity of our approach by applying it to example datasets. AVAILABILITY: The causal analytics tools 'Upstream Regulator Analysis', 'Mechanistic Networks', 'Causal Network Analysis' and 'Downstream Effects Analysis' are implemented and available within Ingenuity Pathway Analysis (IPA, http://www.ingenuity.com). SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.
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