Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/15143
Title: Automated linear motif discovery from protein interaction network
Authors: TAN SOON HENG
Keywords: Computational Biology, Bioinformatics, Motif Discovery, Linear Motif, Protein Interaction Network
Issue Date: 8-Mar-2006
Source: TAN SOON HENG (2006-03-08). Automated linear motif discovery from protein interaction network. ScholarBank@NUS Repository.
Abstract: This thesis describes a new problem of automated motif discovery from protein interaction network to circumvent the bottleneck caused by the lack of prior biological knowledge. We propose a motif pair approach which can extract motifs from sparse interaction data and is robust against noise in input data. Pairs of motifs are mined from similar co-occurring subsequences embedded in pairs of interacting sequences and we model the task as a novel double cliques finding problem. As finding clique is NP-Hard, we designed an algorithm (D-STAR) was designed to find the approximate solutions and validated the algorithm on sets of semi-synthetic and real biological data.
URI: http://scholarbank.nus.edu.sg/handle/10635/15143
Appears in Collections:Master's Theses (Open)

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