Modelling signalling networks from perturbation data.
Bioinformatics
; 34(23): 4079-4086, 2018 12 01.
Article
em En
| MEDLINE
| ID: mdl-29931053
ABSTRACT
Motivation Intracellular signalling is realized by complex signalling networks, which are almost impossible to understand without network models, especially if feedbacks are involved. Modular Response Analysis (MRA) is a convenient modelling method to study signalling networks in various contexts. Results:
We developed the software package STASNet (STeady-STate Analysis of Signalling Networks) that provides an augmented and extended version of MRA suited to model signalling networks from incomplete perturbation schemes and multi-perturbation data. Using data from the Dialogue on Reverse Engineering Assessment and Methods challenge, we show that predictions from STASNet models are among the top-performing methods. We applied the method to study the effect of SHP2, a protein that has been implicated in resistance to targeted therapy in colon cancer, using a novel dataset from the colon cancer cell line Widr and a SHP2-depleted derivative. We find that SHP2 is required for mitogen-activated protein kinase signalling, whereas AKT signalling only partially depends on SHP2. Availability and implementation An R-package is available at https//github.com/molsysbio/STASNet. Supplementary information Supplementary data are available at Bioinformatics online.
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Base de dados:
MEDLINE
Assunto principal:
Software
/
Transdução de Sinais
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article