- Conference Paper
In this work, we proposed a network analysis method called DeltaNeTS for inferring genetic perturbations from temporal transcriptional expression profiles. While several efficacious and robust network analysis methods exist for steady state data, a direct application of these methods to analyze time series expression data often leads to a poor prediction performance. DeltaNeTS is an extension of our previous method DeltaNet, which involves a single-step inference of gene regulatory network and gene targets from transcriptional profiles. In order to prevent reversals in the causal directions of gene regulations when analyzing time series data, DeltaNeTS employs an additional constraint based on the time derivatives of the temporal expression profiles. We demonstrated the advantages of DeltaNeTS over DeltaNet and a network analysis method called Time Series Network Inference (TSNI), by analyzing time-series expression data from in silico simulations and from microarray assays of Saccharomyces cerevisiae (yeast) and cultured human airway epithelial cells. Show more
Book title6th IFAC Conference on Foundations of Systems Biology in Engineering, FOSBE 2016. Proceedings
Journal / seriesIFAC-PapersOnLine
Pages / Article No.
SubjectTime series; Gene expression; Network perturbations; Mechanism of action; Lasso
Organisational unit03898 - Gunawan, Rudiyanto (ehemalig)
MoreShow all metadata