Name
Abstract | ||
|---|---|---|
This paper presents a method for regulatory network reconstruction from experimental data. We propose a mathematical model for regulatory interactions, based on the work of Thomas et al. [25] extended with a stochastic element and provide an algorithm for reconstruction of such models from gene expression time series. We examine mathematical properties of the model and the reconstruction algorithm and test it on expression profiles obtained from numerical simulation of known regulatory networks. We compare the reconstructed networks with the ones reconstructed from the same data using Dynamic Bayesian Networks and show that in these cases our method provides the same or better results. The supplemental materials to this article are available from the website http://bioputer.mimuw.edu.pl/papers/cmsb06 |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11885191_10 | CMSB |
Keywords | Field | DocType |
reconstruction algorithm,mathematical property,expression profile,regulatory interaction,mathematical model,regulatory network reconstruction,stochastic logical network,gene expression time series,regulatory network,experimental data,reconstructed network,gene expression,time series,numerical simulation,dynamic bayesian network | Boolean network,Data mining,Computer simulation,Experimental data,Computer science,Reconstruction algorithm,Bayesian network,Mathematical properties,Dynamic Bayesian network | Conference |
Volume | ISSN | ISBN |
4210 | 0302-9743 | 3-540-46166-3 |
Citations | PageRank | References |
2 | 0.38 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bartek Wilczynski | 1 | 418 | 26.85 |
| Jerzy Tiuryn | 2 | 1210 | 126.00 |