Abstract
Complex networks of interactions between genes, proteins, and other molecules choreograph cellular processes. The interactions that are active in the cell change over time, both as a natural outcome of the cell‘s natural life cycle and in response to external signals. The set of active interactions, called the response network, are likely to be significantly different between a normally-functioning cell and a diseased cell. The wide availability of DNA microarray data and experimentallydetermined interaction networks has made it possible to automatically compute response networks. This chapter surveys algorithms that have been developed to compute response networks.
Keywords
- Gene Expression Data
- Interaction Network
- Protein Interaction Network
- Connected Subgraph
- Gene Expression Dataset
These 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.
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Lasher, C.D., Poirel, C.L., Murali, T.M. (2010). Cellular Response Networks. In: Heath, L., Ramakrishnan, N. (eds) Problem Solving Handbook in Computational Biology and Bioinformatics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09760-2_11
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