Method for Identifying Drug Targets in Biological Networks
This is the extension of the bridging centrality network to biological networks. In the network representation, proteins and other biological molecules are the nodes of a network and the interactions between the molecules are the edges connecting nod es. The degree of a node and and centrality have been proposed as graph theoritic metric that assesses the number of shortest paths passing through a given node. Although target identification with these centrality metrics can potentially locate ta rgets with strong effects, their major weaknesses is in their specificity/selectivity and side effect profiles: lethality cannot be tolerated as an outcome in pharmaceutical development. The proposed invention is based on disrupting signal flow betw een molecules of biological processes instead of disrupting functions of biological processes. Algorithms are developed and metrics is evaluated for identifying and assessing effective information flow disruptive molecular targets in biological netwo rks.
Categories: Research Tool, Bioinformatics
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