Abstract
Identifying drug target is one of the most important tasks in systems biology. In this paper, we develop a method to identify drug targets in biomolecular networks based on the structural output controllability of complex networks. The drug target identification has been formulated as a problem of finding steering nodes in networks. By applying control signals to these nodes, the biomolecular networks can be transited from one state to another. According to the control theory, a graph-theoretic algorithm has been proposed to find a minimum set of steering nodes in biomolecular networks which can be a potential set of drug targets. An illustrative example shows how the proposed method works. Application results of the method to real metabolic networks are supported by existing research results.KeywordsDrug TargetBipartite GraphMetabolic NetworkInput NodeGeneric RankThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
