Browsing by Author "Weighill, Deborah A."

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    3-way networks : application of hypergraphs for modelling increased complexity in comparative genomics
    (PLoS, 2015-03) Weighill, Deborah A.; Jacobson, Daniel A.
    We present and develop the theory of 3-way networks, a type of hypergraph in which each edge models relationships between triplets of objects as opposed to pairs of objects as done by standard network models. We explore approaches of how to prune these 3-way networks, illustrate their utility in comparative genomics and demonstrate how they find relationships which would be missed by standard 2-way network models using a phylogenomic dataset of 211 bacterial genomes.
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    Exploring the topology of complex phylogenomic and transcriptomic networks
    (Stellenbosch : Stellenbosch University, 2014-12) Weighill, Deborah A.; Jacobson, Dan A.; Stellenbosch University. Faculty of AgriScience. Dept. of Institute for Wine Biotechnology.
    ENGLISH ABSTRACT: This thesis involved the development and application of network approaches for the construction, analysis and visualization of phylogenomic and transcriptomic networks. A co-evolutionary network model of grapevine genes was constructed based on three mechanisms of evolution. The investigation of local neighbourhoods of this network revealed groups of functionally related genes, illustrating that the multi-mechanism evolutionary model was identifying groups of potentially co-evolving genes. An extended network definition, namely 3-way networks, was investigated, in which edges model relationships between triplets of objects. Strategies for weighting and pruning these 3-way networks were developed and applied to a phylogenomic dataset of 211 bacterial genomes. These 3-way bacterial networks were compared to standard 2-way network models constructed from the same dataset. The 3-way networks modelled more complex relationships and revealed relationships which were missed by the two-way network models. Network meta-modelling was explored in which global network and node-bynode network comparison techniques were applied in order to investigate the effect of the similarity metric chosen on the topology of multiple types of networks, including transcriptomic and phylogenomic networks. Two new network comparison techniques were developed, namely PCA of Topology Profiles and Cross-Network Topological Overlap. PCA of Topology Profiles compares networks based on a selection of network topology indices, whereas Cross- Network Topological Overlap compares two networks on a node-by-node level, identifying nodes in two networks with similar neighbourhood topology and thus highlighting areas of the networks with conflicting topologies. These network comparison methods clearly indicated how the similarity metric chosen to weight the edges of the network influences the resulting network topology, consequently influencing the biological interpretation of the networks.