In this talk we will present two unrelated methods for constructing networks from molecular sequence data
and from metabolic profiles.

Phylogenetic networks are a generalization of phylogenetic trees that permit the representation of conflicting signal or alternative phylogenetic histories. Networks can provide a useful tool for phylogenetic analysis when the underlying evolutionary history is non treelike. For example, recombination, hybridization, and lateral gene transfer can all lead to histories that are not adequately represented by a single tree. In the first part
of the talk, we present some techniques for the whole-genome scale construction of phylogenetic networks.

The second part of the talk is concerned with reconstruction of metabolic networks. A well-studied problem in biochemical system analysis is the reconstruction of model parameters from metabolic profiles. Due to the high dimensionality of this problem, most current methods for its solution are based on heuristic algorithms. However, such methods often produce point estimates for parameters, with no guarantees of accuracy. Here, we present an alternative way to solve the reconstruction problem that is based on the mathematical theory of interval analysis that has the advantage of providing reliable estimates of parameters.