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Cellular Regulatory Network Modeling Applied to Breast Cancer

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Networks in Systems Biology

Part of the book series: Computational Biology ((COBO,volume 32))

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Abstract

Cells in an organism interact with each other and with the environment through a complex set of signals, which triggers responses and activates cellular regulation mechanisms. Models obtained by computational mathematics for cellular signaling dynamics are used to understand factors and causes of deregulation of internal biological processes, which is a relevant knowledge in a disease such as cancer. Gene regulatory networks describe gene interactions and how these relationships control cellular processes such as growth and cell division, which relate this disease to the regulatory network. Despite its simplicity, Boolean networks may accurately model some biological phenomena, such as gene regulatory network dynamics. Indeed, several reports in the literature show that they are accurate enough to build models of regulatory networks of cell lines related to breast cancer. In this chapter, we present a methodology for building cellular regulatory networks based on the Boolean paradigm, which uses entropy as a criterion for selecting genes that are included in the network. The main objective is to understand dynamical behaviors related to situations that cause breast cancer and tumor lineages and to suggest experimentations to verify the outcome of interventions in networks, in order to support the identification of new therapeutic targets.

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Author information

Authors and Affiliations

  1. State University of Rio de Janeiro - UERJ - Rua São Francisco Xavier, 524 Maracanã, Rio de Janeiro, Brazil

    Luiz Henrique Oliveira Ferreira & Maria Clicia Stelling de Castro

  2. Plataforma de Modelagem de Sistemas Biológicos, Center of Technology Development in Health, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil

    Alessandra Jordano Conforte & Nicolas Carels

  3. Laboratório de Modelagem Computacional de Sistemas Biológicos, Scientific Computing Program (PROCC), Oswaldo Cruz Foundation, Rio de Janeiro, Brazil

    Alessandra Jordano Conforte & Fabrício Alves Barbosa da Silva

Authors
  1. Luiz Henrique Oliveira Ferreira
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  2. Maria Clicia Stelling de Castro
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  3. Alessandra Jordano Conforte
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  4. Nicolas Carels
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  5. Fabrício Alves Barbosa da Silva
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Correspondence to Fabrício Alves Barbosa da Silva .

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Editors and Affiliations

  1. Scientific Computing Program (PROCC), Oswaldo Cruz Foundation, Rio de Janeiro, Brazil

    Fabricio Alves Barbosa da Silva

  2. CDTS, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil

    Nicolas Carels

  3. Department of Computational Modeling, National Laboratory of Scientific Computing, Petrópolis, Rio de Janeiro, Brazil

    Marcelo Trindade dos Santos

  4. Graduate Program in Nanobiosystems, Federal University of Rio de Janeiro, Duque de Caxias, Rio de Janeiro, Brazil

    Francisco José Pereira Lopes

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Ferreira, L.H.O., de Castro, M.C.S., Conforte, A.J., Carels, N., da Silva, F.A.B. (2020). Cellular Regulatory Network Modeling Applied to Breast Cancer. In: da Silva, F.A.B., Carels, N., Trindade dos Santos, M., Lopes, F.J.P. (eds) Networks in Systems Biology. Computational Biology, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-030-51862-2_13

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  • DOI: https://doi.org/10.1007/978-3-030-51862-2_13

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