Reconstructing the topology of a signaling network by means of RNA interference (RNAi) technology is an underdetermined problem especially when a single gene in the network is knocked down or observed. In addition, the exponential search space limits the existing methods to small signaling networks of size 10-15 genes. In this thesis, we propose integrating RNAi data with a reference physical interaction network. We formulate the problem of signaling network reconstruction as finding the minimum number of edit operations on a given reference network. The edit operations transform the reference network to a network that satisfy the RNAi observations. We show that using a reference network does not simplify the computational complexity of the problem. Therefore, we propose an approach that provides near optimal results and can scale well for reconstructing networks up to hundreds of components. We validate the proposed method on synthetic and real datasets. Comparison with the state of the art on real signaling networks shows that the proposed methodology can scale better and generates biologically significant results.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12614586/index.pdf |
| Date | 01 September 2012 |
| Creators | Hashemikhabir, Seyedsasan |
| Contributors | Can, Tolga |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | Access forbidden for 1 year |
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