TY - JOUR AU - Lemos, Alexandre AU - Lynce, InĂªs AU - Monteiro, Pedro T. PY - 2019 DA - 2019/03/25 TI - Repairing Boolean logical models from time-series data using Answer Set Programming JO - Algorithms for Molecular Biology SP - 9 VL - 14 IS - 1 AB - 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, where the process is still manually performed and therefore slow and prone to errors. SN - 1748-7188 UR - https://doi.org/10.1186/s13015-019-0145-8 DO - 10.1186/s13015-019-0145-8 ID - Lemos2019 ER -