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期刊名称: Bioinformatics
Volume:30    Issue:4        Page:523-530
ISSN:1367-4803

Causal analysis approaches in ingenuity pathway analysis期刊论文

作者: Krämer Andreas Green Jeff Pollard Jack Tugendreich Stuart
DOI:10.1093/bioinformatics/btt703

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页码: 523-530
被引频次: 918
出版者: OXFORD UNIV PRESS,Oxford University Press
期刊名称: Bioinformatics
ISSN: 1367-4803
卷期: Volume:30    Issue:4
语言: English
摘要: Motivation: Prior 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. Results: We 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.
相关主题: BREAST-CANCER CELLS, BIOTECHNOLOGY & APPLIED MICROBIOLOGY, MCF-7, MOUSE, BIOCHEMICAL RESEARCH METHODS, MATHEMATICAL & COMPUTATIONAL BIOLOGY, TRANS-RETINOIC ACID, Knowledge Bases, Algorithms, Breast Neoplasms - genetics, Human Umbilical Vein Endothelial Cells - metabolism, MCF-7 Cells, Humans, Computational Biology, Female, Gene Expression Profiling - methods, Causality, Gene Regulatory Networks, Index Medicus, Original Papers,

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