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Network Controllability Analysis of Three Multiple-myeloma Patient Genetic Mutation Datasets

Jose Angel Sanchez Martin, Ion Petre, Network Controllability Analysis of Three Multiple-myeloma Patient Genetic Mutation Datasets. TUCS Technical Reports 1206, TUCS, 2019.

Abstract:

Network controllability focuses on the concept of driving the dynamical system associated to a directed network of interactions from an arbitrary initial state to an arbitrary final state, through a well-chosen set of input functions applied in a minimal number of so-called driver nodes. In earlier studies we and other groups demonstrated the potential of applying this concept in medicine. A directed network of interactions may be built around the main known drivers of the disease being studies, and then analysed to identify combinations of drug targets controlling survivability-essential genes in the network. This paper takes the next step and focuses on patient data. We demonstrate that comprehensive protein-protein interaction networks can be built around patient genetic data, and that network controllability can be used to identify possible personalised drug combinations. We discuss the algorithmic methods that can be used to construct and analyse these networks.

BibTeX entry:

@TECHREPORT{tSaPe19a,
  title = {Network Controllability Analysis of Three Multiple-myeloma Patient Genetic Mutation Datasets},
  author = {Sanchez Martin, Jose Angel and Petre, Ion},
  number = {1206},
  series = {TUCS Technical Reports},
  publisher = {TUCS},
  year = {2019},
}

Belongs to TUCS Research Unit(s): Computational Biomodeling Laboratory (Combio Lab)

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