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Title: Conserved gene cluster discovery and applications in comparative genomics
Keywords: computational biology, conserved gene cluster, ortholog assignment, algorithms, comparative genomics
Issue Date: 19-Aug-2011
Citation: ZHANG ZHIYONG MELVIN (2011-08-19). Conserved gene cluster discovery and applications in comparative genomics. ScholarBank@NUS Repository.
Abstract: Conserved gene clusters are sets of genes that are located close to one another in the genomes of several species. Two popular models of conserved gene clusters are the max-gap and max-length model. A common problem with applying these models is figuring out appropriate model parameters. We developed an efficient algorithm to compute max-length clusters for every value of the max-gap parameter and represent the clusters in a compact structure, the Gene Team Tree (GTT). We restrict the max-length model by imposing the bidirection best hit criteria. This additional restriction allowed us to develop efficient algorithms for finding all clusters. In silico experiments show that our restricted max-length model (BBHRW) is better than the max-gap model for modelling operons in prokaryotes. Accurate identification of conserved gene clusters depends on our ability to detect conserved genes. We design a simple, yet effective method (BBH-LS) that combines sequence and gene context similarity to infer one-to-one gene pairs between two species. BBH-LS outperforms more sophisticated methods based on genome rearrangements and phylogenetic reconstruction.
Appears in Collections:Ph.D Theses (Open)

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