Towards a semi-automatic model revision of logical regulatory network (IFCT)

Type: National Project Project

Duration: from 2015 Jan 01 to 2018 Dec 31

Financed by: FCT

Prime Contractor: IF/01333/2013/CP1 204/CT0001 (Other)

The foremost question in Systems Biology is how to interpret vast amount of multiscale data, in order to predict and explain the behavior of complex biological systems. The present proposal addresses this question and is subdivided into two main interconnected parts: methods and applications. A comparative genomics approach will be used among closely related species, for the identification of a comprehensive regulatory network scaffold (top-down). Then starting with homologous regulatory elements we will proceed with the definition of a logical model (bottom-up), complemented with formal verification techniques for model analysis and validation. Additionally, methods aimed at the full characterization of complex cyclic attractors, which is still an open problem, will be developed using the circuit functionality contexts. These methods will be applied to the prediction of Multidrug Resistance in yeasts due to its importance on the control of highly opportunistic pathogen on human impaired immune system [20]. Also, using the Segment Polarity cross-regularity module to simulate a 2D grid cross-signaling of cells O will push the limits of current logical regulatory networks.


  • INESC-ID (Other)

Principal Investigators