Pathway network inference from gene expression data
نویسندگان
چکیده
منابع مشابه
Bagging Statistical Network Inference from Large-Scale Gene Expression Data
Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper,...
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In this paper we introduce a new inference method of a gene regulatory network from steady-state gene expression data. Our method determines a regulatory structure consistent with an observed set of steady-state expression profiles, each generated from wild-type and single deletion mutant of the target network. Our method derives the regulatory relationships in the network using a graph theoret...
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MOTIVATION Markov networks are undirected graphical models that are widely used to infer relations between genes from experimental data. Their state-of-the-art inference procedures assume the data arise from a Gaussian distribution. High-throughput omics data, such as that from next generation sequencing, often violates this assumption. Furthermore, when collected data arise from multiple relat...
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ژورنال
عنوان ژورنال: BMC Systems Biology
سال: 2014
ISSN: 1752-0509
DOI: 10.1186/1752-0509-8-s2-s7