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• W2010134474 abstract "A Signal transduction pathway is the chain of processes by which a cell converts an extracellular signal into a response. In most unicellular organisms, the number of signal transduction pathways influences the number of ways the cell can react and respond to the environment. Discovering signal transduction pathways is an arduous problem, even with the use of systematic genomic, proteomic and metabolomic technologies. These techniques lead to an enormous amount of data and how to interpret and process this data becomes a challenging computational problem. In this study we present a new framework for identifying signaling pathways in protein-protein interaction networks. Our goal is to find biologically significant pathway segments in a given interaction network. Currently, protein-protein interaction data has excessive amount of noise, e.g., false positive and false negative interactions. First, we eliminate false positives in the protein-protein interaction network by integrating the network with microarray expression profiles, protein subcellular localization and sequence information. In addition, protein families are used to repair false negative interactions. Then the characteristics of known signal transduction pathways and their functional annotations are extracted in the form of association rules. Given a pair of starting and ending proteins, our methodology returns candidate pathway segments between these two proteins with possible missing links (recovered false negatives). In our study, S. cerevisiae (yeast) data is used to demonstrate the effectiveness of our method." @default.
• W2010134474 created "2016-06-24" @default.
• W2010134474 creator A5008925587 @default.
• W2010134474 creator A5010008442 @default.
• W2010134474 date "2007-09-13" @default.
• W2010134474 modified "2023-10-17" @default.
• W2010134474 title "PathFinder: mining signal transduction pathway segments from protein-protein interaction networks" @default.
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• W2010134474 doi "https://doi.org/10.1186/1471-2105-8-335" @default.
• W2010134474 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2100073" @default.
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• W2010134474 hasPublicationYear "2007" @default.
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