2011
DOI: 10.1371/journal.pone.0024702
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A Differential Network Approach to Exploring Differences between Biological States: An Application to Prediabetes

Abstract: BackgroundVariations in the pattern of molecular associations are observed during disease development. The comprehensive analysis of molecular association patterns and their changes in relation to different physiological conditions can yield insight into the biological basis of disease-specific phenotype variation.MethodologyHere, we introduce a formal statistical method for the differential analysis of molecular associations via network representation. We illustrate our approach with extensive data on lipopro… Show more

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Cited by 37 publications
(29 citation statements)
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“…Similarly, metabolic networks assembled from correlated activities of liver metabolites were differentially compared between normal and diabetic conditions to identify functional regulators of diabetic dyslipidemias in humans 143 . It is likely that continued advances in differential network mapping and analysis will shed light on tissue-specific, spatio-temporal and dosage-dependent rewiring of biological networks.…”
Section: ‘Differential’ Network Modulesmentioning
confidence: 99%
“…Similarly, metabolic networks assembled from correlated activities of liver metabolites were differentially compared between normal and diabetic conditions to identify functional regulators of diabetic dyslipidemias in humans 143 . It is likely that continued advances in differential network mapping and analysis will shed light on tissue-specific, spatio-temporal and dosage-dependent rewiring of biological networks.…”
Section: ‘Differential’ Network Modulesmentioning
confidence: 99%
“…17,18 Recent interaction mapping studies have demonstrated the power of differential correlation analysis for elucidating the re-wiring of the interaction architecture of fundamental biological responses in adaptation to changing conditions. [19][20][21][22][23][24][25] Analyzing the rewiring of biological networks across disease conditions provides a unique insight into the dynamic response of a biological system. Instead of looking at the absolute properties of a system, differential network analysis emphasizes on the characteristics that are the most affected by genetic or environmental influences.…”
Section: Introductionmentioning
confidence: 99%
“…In contrast with conventional gene-based methods, by performing the differential network analysis, more characteristic genes or subnetworks known to be related to disease development are identified. Valcárcel et al [16] inferred a differential network from males with normal fasting glucose (NFG) and impaired fasting glucose (IFG), in which shrinkage estimates of the partial correlation are executed for network construction, and then the differences were explored by utilizing statistical tests between the two defined groups (NFG and IFG). Gambardella et al [17] developed a powerful procedure named DINA to identify tissue-specific pathways using a slightly modified information entropy measure.…”
Section: Introductionmentioning
confidence: 99%