Name
Abstract | ||
|---|---|---|
In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes.In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process.The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1093/bioinformatics/btn336 | Bioinformatics |
Keywords | Field | DocType |
cellular differentiation process,stable steady state,multiple gene perturbation protocol,correct steady state identification,gene regulatory network,cell differentiation process,protein interaction,silico modeling,th2 cellular differentiation process,boolean modeling,asynchronous modeling,biological systems,boolean model,cellular differentiation,cell differentiation,steady state | Attractor,Asynchronous communication,Large networks,Computer science,Binary decision diagram,Theoretical computer science,Software,Bioinformatics,Gene regulatory network,In silico | Journal |
Volume | Issue | ISSN |
24 | 17 | 1367-4811 |
Citations | PageRank | References |
80 | 3.91 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abhishek Garg | 1 | 187 | 11.66 |
| Alessandro Di Cara | 2 | 138 | 7.41 |
| Ioannis Xenarios | 3 | 2301 | 293.04 |
| luis mendoza | 4 | 271 | 25.94 |
| Giovanni De Micheli | 5 | 10245 | 1018.13 |