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Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Reconstructing the temporal progression of HIV-1 immune response pathways.
Bioinformatics 2016 June 16
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.
AVAILABILITY AND IMPLEMENTATION: Data, Supplementary text and the TimePath software are available from https://sb.cs.cmu.edu/timepath
CONTACT: [email protected]
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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.
AVAILABILITY AND IMPLEMENTATION: Data, Supplementary text and the TimePath software are available from https://sb.cs.cmu.edu/timepath
CONTACT: [email protected]
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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