Infer gene regulatory networks from time series data with formal methods

Michele Ceccarelli, Luigi Cerulo, Antonella Santone

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Reverse engineering of regulatory relationships from genomics data is emerging as crucial to dissect the complex underlying regulatory mechanism occurring in a cell. In this paper we propose a novel reverse engineering algorithm that makes use of formal methods, usually adopted in engineering to specify and verify concurrent software and hardware systems. With a formal specification of gene regulatory hypotheses we are able to prove mathematically whether a time course experiment belongs or not to the formal specification, determining in fact whether a gene regulation exists or not. The method is capable to detect both direction and sign (inhibition/activation) of regulations whereas most of literature methods which are limited to undirected and/or unsigned relationships. The method, empirically evaluated on experimental and synthetic datasets, reaches high levels of accuracy, outperforming literature methods in terms of precision and recall, despite the computational cost increases exponentially with the size of the network.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
Pages115-120
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2013
Externally publishedYes
Event2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013 - Shanghai, China
Duration: 18 Dec 201321 Dec 2013

Other

Other2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
CountryChina
CityShanghai
Period18/12/1321/12/13

Fingerprint

Formal methods
Reverse engineering
Time series
Genes
Gene expression
Chemical activation
Hardware
Costs
Experiments
Formal specification
Genomics

Keywords

  • Formal Methods
  • Gene Regulatory Network
  • Reverse Engineering

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Ceccarelli, M., Cerulo, L., & Santone, A. (2013). Infer gene regulatory networks from time series data with formal methods. In Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013 (pp. 115-120). [6732473] https://doi.org/10.1109/BIBM.2013.6732473

Infer gene regulatory networks from time series data with formal methods. / Ceccarelli, Michele; Cerulo, Luigi; Santone, Antonella.

Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013. 2013. p. 115-120 6732473.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ceccarelli, M, Cerulo, L & Santone, A 2013, Infer gene regulatory networks from time series data with formal methods. in Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013., 6732473, pp. 115-120, 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013, Shanghai, China, 18/12/13. https://doi.org/10.1109/BIBM.2013.6732473
Ceccarelli M, Cerulo L, Santone A. Infer gene regulatory networks from time series data with formal methods. In Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013. 2013. p. 115-120. 6732473 https://doi.org/10.1109/BIBM.2013.6732473
Ceccarelli, Michele ; Cerulo, Luigi ; Santone, Antonella. / Infer gene regulatory networks from time series data with formal methods. Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013. 2013. pp. 115-120
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