Abstract
This paper begins to build a theoretical framework that would enable the pharmaceutical industry to use network complexity measures as a way to identify drug targets. The variability of a betweenness measure for a network node is examined through different methods of network perturbation. Our results indicate a robustness of betweenness centrality in the identification of target genes.
Keywords:
Betweenness centrality; Differential expression; Network complexity measure.
Publication types
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Research Support, N.I.H., Extramural
MeSH terms
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Algorithms
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Astrocytoma / genetics
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Astrocytoma / metabolism
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Brain Neoplasms / genetics
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Brain Neoplasms / metabolism
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Confidence Intervals
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Databases, Genetic / statistics & numerical data
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Drug Development / statistics & numerical data
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Gene Expression Profiling / statistics & numerical data
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Gene Regulatory Networks*
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Genes, Essential*
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Humans
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Mathematical Concepts
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Models, Genetic*
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Neoplasms / genetics
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Neoplasms / metabolism
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Protein Interaction Maps
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Statistics, Nonparametric
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Systems Biology / statistics & numerical data