May 24, 2016

Personalized characterization of diseases using sample-specific networks

BioRxiv : the Preprint Server for Biology
XiaoPing LiuLuoNan Chen


A complex disease generally results not from malfunction of individual molecules but from dysfunction of the relevant system or network, which dynamically changes with time and conditions. Thus, estimating a condition-specific network from a sample is crucial to elucidating the molecular mechanisms of complex diseases at the system level. However, there is currently no effective way to construct such an individual-specific network by expression profiling of a single sample because of the requirement of multiple samples for computing correlations. We developed here with a statistical method, i.e., a sample-specific network method, which allows us to construct individual-specific networks based on molecular expression of a single sample. Using this method, we can characterize various human diseases at a network level. In particular, such sample-specific networks can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information. Extensive analysis by using the Cancer Genome Atlas data not only demonstrated the effectiveness of the method, but also found new individual-specific driver genes and network patterns for various cancers. Biological experiments on drug ...Continue Reading

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Mentioned in this Paper

Nucleic Acid Sequencing
Molecular Profiling
Resistance Process
Drug Resistance
Statistical Technique
Malignant Neoplasms

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