Topology of molecular interaction networks

Abstract Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks. Initial studies suggested that molecular interaction network topology is related to biological function and evolution. However, further whole-network analyses did not lead to a unified view on what this relation may look like, with conclusions highly dependent on the type of molecular interactions considered and the metrics used to study them. It is unclear whether global network topology drives function, as suggested by some researchers, or whether it is simply a byproduct of evolution or even an artefact of representing complex molecular interaction networks as graphs. Nevertheless, network biology has progressed significantly over the last years. We review the literature, focusing on two major developments. First, realizing that molecular interaction networks can be naturally decomposed into subsystems (such as modules and pathways), topology is increasingly studied locally rather than globally. Second, there is a move from a descriptive approach to a predictive one: rather than correlating biological network 1 topology to generic properties such as robustness, it is used to predict specific functions or phenotypes. Taken together, this change in focus from globally descriptive to locally predictive points to new avenues of research. In particular, multi-scale approaches are developments promising to drive the study of molecular interaction networks further

The crossing number of a graph in the plane

Thesis (MSc (Mathematical Sciences. Applied Mathematics))--University of Stellenbosch, 2005.Heuristics for obtaining upper bounds on crossing numbers of small graphs in the plane, and a heuristic for obtaining lower bounds to the crossing numbers of large graphs in the plane are presented in this thesis. It is shown that the two-page book layout framework is effective for deriving general upper bounds, and that it may also be used to obtain exact results for the crossing numbers of graphs. The upper bound algorithm is based on the well-kown optimization heuristics of tabu search, genetic algorithms and neural networks for obtaining two-page book layouts with few resultant edge crossings. The lower bound algorithm is based on the notion of embedding a graph into another graph, and, to the best knowledge of the author, it is the first known lower bound algorithm for the corssing number of a graph. It utilizes Dijkstra's shortest paths algorithm to embed one graph into another, in such a fashion as to minimize edge and vertex congestion values. The upper bound algorithms that were developed in this thesis were applied to all non-planar complete multipartite graphs of orders 6-13. A catalogue of drawings of these graphs with low numbers of crossings is provided in the thesis. Lower bounds on the crossing numbers of these graphs were also computed, using lowerbounds that are known for a number of complete multipartite graphs, as well as the fact that lower bounds on the crossing numbers of the subgraphs of a graph G, are lower bounds on the crossing number of G. A reference implementation of the Garey-Johnson algorithm is supplied, and finally, it is shown that Szekely's algorithm for computing the independent-odd crossing number may be converted into a heuristic algorithm for deriving upper bounds on the plane crossing number of a graph. This thesis also provides a thorough survey of results known for the crossing number of a graph in the plane. The survey especially focuses on algorithmic issues that have been proposed by researchers in the field of crossing number research