### Abstract

Original language | English |
---|---|

Pages (from-to) | 38-44 |

Number of pages | 9 |

Journal | Journal of Theoretical Biology |

Volume | 403 |

Early online date | 14 May 2016 |

DOIs | |

Publication status | Published - 21 Aug 2016 |

### Fingerprint

### Keywords

- q-bio.MN
- relational biology
- (M, R)-system
- complex networks
- random walks
- theoretical KOs

### Cite this

*Journal of Theoretical Biology*,

*403*, 38-44. https://doi.org/10.1016/j.jtbi.2016.05.021

**Theoretical knock-outs on biological networks.** / Miranda, Pedro J (Corresponding Author); Pinto, Sandro E de S; Baptista, Murilo S; La Guardia, Giuliano G.

Research output: Contribution to journal › Article

*Journal of Theoretical Biology*, vol. 403, pp. 38-44. https://doi.org/10.1016/j.jtbi.2016.05.021

}

TY - JOUR

T1 - Theoretical knock-outs on biological networks

AU - Miranda, Pedro J

AU - Pinto, Sandro E de S

AU - Baptista, Murilo S

AU - La Guardia, Giuliano G

PY - 2016/8/21

Y1 - 2016/8/21

N2 - In this work we formalize a method to compute the degree of importance of biological agents that participates on the dynamics of a biological phenomenon build upon a complex network. We call this new procedure by theoretical knock-out (KO). To devise this method, we make two approaches: algebraically and algorithmically. In both cases we compute a vector on an asymptotic state, called flux vector. The flux is given by a random walk on a directed graph that represents a biological phenomenon. This vector gives us the information about the relative flux of walkers on a vertex which represents a biological agent. With two vector of this kind, we can calculate the relative mean error between them by averaging over its coefficients. This quantity allows us to assess the degree of importance of each vertex of a complex network that evolves in time and has experimental background. We find out that this procedure can be applied in any sort of biological phenomena in which we can know the role and interrelationships of its agents. These results also provide experimental biologists to predict the order of importance of biological agents on a mounted complex network.

AB - In this work we formalize a method to compute the degree of importance of biological agents that participates on the dynamics of a biological phenomenon build upon a complex network. We call this new procedure by theoretical knock-out (KO). To devise this method, we make two approaches: algebraically and algorithmically. In both cases we compute a vector on an asymptotic state, called flux vector. The flux is given by a random walk on a directed graph that represents a biological phenomenon. This vector gives us the information about the relative flux of walkers on a vertex which represents a biological agent. With two vector of this kind, we can calculate the relative mean error between them by averaging over its coefficients. This quantity allows us to assess the degree of importance of each vertex of a complex network that evolves in time and has experimental background. We find out that this procedure can be applied in any sort of biological phenomena in which we can know the role and interrelationships of its agents. These results also provide experimental biologists to predict the order of importance of biological agents on a mounted complex network.

KW - q-bio.MN

KW - relational biology

KW - (M, R)-system

KW - complex networks

KW - random walks

KW - theoretical KOs

U2 - 10.1016/j.jtbi.2016.05.021

DO - 10.1016/j.jtbi.2016.05.021

M3 - Article

VL - 403

SP - 38

EP - 44

JO - Journal of Theoretical Biology

JF - Journal of Theoretical Biology

SN - 0022-5193

ER -