De Novo Signaling Pathway Reconstruction From Multiple Data Sources
msra
摘要
Abstract Signaling pathways are the primary means of regulating cell growth, metabolism, differentiation and apoptosis. The de novo signaling pathway reconstruction problem can be divided into two sub-problems: discovery of pathway components and ordering the pathway components. While the literature abounds with computational and biological approaches for discovering pathway components, there has only been limited research on ordering pathway components, despite its importance. The main biological approach, genetic epitasis analysis, is limited by the cost and unavailability of mutants. Existing computational approaches reconstruct the network from numerical data (e.g., microarray gene expression profiles) which may be unreliable. Consequently, these approaches are sensitive to data selection. Here we describe a new statistical approach to signaling network reconstruction exploiting information about the set of genes belonging to each pathway to reconstruct the “gene regulation network topology” in the form of a first-order
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