Reconstructing the temporal progression of HIV-1 immune response pathways

Abstract

Motivation: Most methods for reconstructing response networks from high throughput data generate static models which cannot distinguish between early and late response stages. Results: We present TimePath, a new method that integrates time series and static datasets to reconstruct dynamic models of host response to stimulus. TimePath uses an Integer Programming formulation to select a subset of pathways that, together, explain the observed dynamic responses. Applying TimePath to study human response to HIV-1 led to accurate reconstruction of several known regulatory and signaling pathways and to novel mechanistic insights. We experimentally validated several of TimePaths' predictions highlighting the usefulness of temporal models.