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B47 Cross-integration of huntington’s disease networks
  1. François-Xavier Lejeune1,2,
  2. Hélissande Fragnaud1,2,
  3. Frédéric Parmentier1,2,
  4. Erwan Bigan1,2,
  5. Satish Sasidharan Nair1,2,
  6. Christian Neri1,2
  1. 1Institut of Biology Paris-Seine (IBPS), UMR 8256, Paris, France
  2. 2Paris-Sorbonne University, University Pierre and Marie Curie (UPMC), Paris, France


Network methods are useful for reducing data complexity and modelling biological and pathogenic processes on a system level, thus having strong potential for prioritising testable hypotheses in Huntington’s disease (HD) research. Several types of mathematical formalisms are being used for network analysis of signal variability in HD datasets, each of them shedding particular light on transcriptional codes and network dynamics in HD. We tested for HD sub-graphs that may be consistently highlighted by several of these mathematical formalisms and whether this may be linked to specific features of the HD process and translate into a more selective level of gene prioritisation. We will present data based on integrating two types of HD networks and discuss how network comparison methods may add value to systems modelling in HD.

  • data integration
  • network analysis
  • target prioritisation

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