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Predicting Node Characteristics from Molecular Networks

  • Sara Mostafavi
  • Anna Goldenberg
  • Quaid Morris
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 781)

Abstract

A large number of genome-scale networks, including protein–protein and genetic interaction networks, are now available for several organisms. In parallel, many studies have focused on analyzing, characterizing, and modeling these networks. Beyond investigating the topological characteristics such as degree distribution, clustering coefficient, and average shortest-path distance, another area of particular interest is the prediction of nodes (genes) with a given characteristic (labels) – for example prediction of genes that cause a particular phenotype or have a given function. In this chapter, we describe methods and algorithms for predicting node labels from network-based datasets with an emphasis on label propagation algorithms (LPAs) and their relation to local neighborhood methods.

Key words

Functional linkage networks Gene function prediction Label propagation 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Sara Mostafavi
    • 1
  • Anna Goldenberg
    • 2
  • Quaid Morris
    • 3
    • 4
  1. 1.Department of Computer Science, Centre for Cellular and Biomolecular Research (CCBR)University of TorontoTorontoCanada
  2. 2.Banting and Best Department of Medical Research, Centre for Cellular and Biomolecular ResearchUniversity of TorontoTorontoCanada
  3. 3.Department of Computer Science, Banting and Best Department of Medical ResearchCentre for Cellular and Biomolecular ResearchTorontoCanada
  4. 4.Department of Molecular GeneticsUniversity of TorontoTorontoCanada

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