Repairing Boolean logical models from time-series data using Answer Set Programming

Volume: 14, Issue: 1
Published: Mar 25, 2019
Abstract
Boolean models of biological signalling-regulatory networks are increasingly used to formally describe and understand complex biological processes. These models may become inconsistent as new data become available and need to be repaired. In the past, the focus has been shed on the inference of (classes of) models given an interaction network and time-series data sets. However, repair of existing models against new data is still in its infancy,...
Paper Details
Title
Repairing Boolean logical models from time-series data using Answer Set Programming
Published Date
Mar 25, 2019
Volume
14
Issue
1
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