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Automatic Discovery of Combined Drug Therapy

Vladimir Rogojin, Keivan Kazemi, Krishna Kanhaiya, Eugen Czeizler, Ion Petre, Automatic Discovery of Combined Drug Therapy. In: Andrea Bracciali, David Gilbert, Gilbert MacKenzie (Eds.), Thirteenth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, University of Stirling, UK, 2016.

Abstract:

Recent results in network science have demonstrated that network control theory can lead to the development of novel therapeutic approaches for systemic diseases like cancer through the computational analysis of the structure of intracellular molecular interaction networks. These networks are a formal representation of relations between numerous components within cells that are used as a mean for formal holistic reasoning about biological structures. In particular, network controllability studies focus on discovering combinations of external interventions that can drive the biological system to a desired configuration. In practice, these studies can be translated into finding a combined multi-drug therapy in order to achieve a desired response from a cell. We develop a pipeline that finds a minimal set of nodes controlling a given set of targets within a network. The pipeline highlights those control nodes for which there are known FDA approved drugs. The network is generated automatically through quering of a number of pathway databases. The pipeline is deployed as an online web-service.

BibTeX entry:

@INPROCEEDINGS{inpRoKaKaCzPe16a,
  title = {Automatic Discovery of Combined Drug Therapy},
  booktitle = {Thirteenth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics},
  author = {Rogojin, Vladimir and Kazemi, Keivan and Kanhaiya, Krishna and Czeizler, Eugen and Petre, Ion},
  editor = {Bracciali, Andrea and Gilbert, David and MacKenzie, Gilbert},
  publisher = {University of Stirling, UK},
  year = {2016},
  keywords = {bioinformatics pipeline, combinatorial drug discovery, automatic discovery, network modeling, target network control, structural network control, intracellular molecular interaction networks, FDA approved drugs},
}

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

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