Shin_2018_EGFR-PYK2-c-Met interaction network_model
Ontology highlight
ABSTRACT:
SUBMITTER: 
Johannes Meyer
PROVIDER: BIOMD0000000826 | BioModels | 2019-09-27
REPOSITORIES: BioModels
Publications
Systems modelling of the EGFR-PYK2-c-Met interaction network predicts and prioritizes synergistic drug combinations for triple-negative breast cancer.
Shin Sung-Young SY Müller Anna-Katharina AK Verma Nandini N Lev Sima S Nguyen Lan K LK
PLoS computational biology 20180619 6
Prediction of drug combinations that effectively target cancer cells is a critical challenge for cancer therapy, in particular for triple-negative breast cancer (TNBC), a highly aggressive breast cancer subtype with no effective targeted treatment. As signalling pathway networks critically control cancer cell behaviour, analysis of signalling network activity and crosstalk can help predict potent drug combinations and rational stratification of patients, thus bringing therapeutic and prognostic ...[more]
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