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Reconstruction of Signaling Network from Protein Interactions Based on Function Annotations

Published: 01 March 2013 Publication History

Abstract

The directionality of protein interactions is the prerequisite of forming various signaling networks, and the construction of signaling networks is a critical issue in the discovering the mechanism of the life process. In this paper, we proposed a novel method to infer the directionality in protein-protein interaction networks and furthermore construct signaling networks. Based on the functional annotations of proteins, we proposed a novel parameter GODS and established the prediction model. This method shows high sensitivity and specificity to predict the directionality of protein interactions, evaluated by fivefold cross validation. By taking the threshold value of GODS as 2, we achieved accuracy 95.56 percent and coverage 74.69 percent in the human test set. Also, this method was successfully applied to reconstruct the classical signaling pathways in human. This study not only provided an effective method to unravel the unknown signaling pathways, but also the deeper understanding for the signaling networks, from the aspect of protein function.

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  1. Reconstruction of Signaling Network from Protein Interactions Based on Function Annotations

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      Published In

      cover image IEEE/ACM Transactions on Computational Biology and Bioinformatics
      IEEE/ACM Transactions on Computational Biology and Bioinformatics  Volume 10, Issue 2
      March 2013
      272 pages

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      IEEE Computer Society Press

      Washington, DC, United States

      Publication History

      Published: 01 March 2013
      Published in TCBB Volume 10, Issue 2

      Author Tags

      1. Accuracy
      2. Bioinformatics
      3. Humans
      4. Predictive models
      5. Protein engineering
      6. Proteins
      7. Signaling network
      8. Training
      9. cross validation
      10. gene ontology
      11. protein interaction

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