Linear matrix inequalities approach to reconstruction of biological networks

Author

Cosentino, C. ; Curatola, W. ; Montefusco, F. ; Bansal, M. ; di Bernardo, D. ; Amato, F.

Author_Institution

Sch. of Comput. & Biomed. Eng., Univ. degli Studi Magna Graecia di Catanzaro

Volume

1

Issue

3

fYear

2007

fDate

5/1/2007 12:00:00 AM

Firstpage

164

Lastpage

173

Abstract

The general problem of reconstructing a biological interaction network from temporal evolution data is tackled via an approach based on dynamical linear systems identification theory. A novel algorithm, based on linear matrix inequalities, is devised to infer the interaction network. This approach allows to directly taking into account, within the optimisation procedure, the a priori available knowledge of the biological system. The effectiveness of the proposed algorithm is statistically validated, by means of numerical tests, demonstrating how the a priori knowledge positively affects the reconstruction performance. A further validation is performed through an in silico biological experiment, exploiting the well-assessed cell-cycle model of fission yeast developed by Novak and Tyson

Keywords

biology computing; cellular biophysics; microorganisms; biological experiment; biological interaction network; biological networks; biological system; cell-cycle model; dynamical linear systems identification; fission yeast; linear matrix inequalities; statistically validated; temporal evolution data;

fLanguage

English

Journal_Title

Systems Biology, IET

Publisher

iet

ISSN

1751-8849

Type

jour

Filename

4216751