Reconstruction of time-consistent species trees

Background The history of gene families—which are equivalent to event-labeled gene trees—can to some extent be reconstructed from empirically estimated evolutionary event-relations containing pairs of orthologous, paralogous or xenologous genes. The question then arises as whether inferred event-labeled gene trees are “biologically feasible” which is the case if one can find a species tree with which the gene tree can be reconciled in a time-consistent way. Results In this contribution, we consider event-labeled gene trees that contain speciations, duplications as well as horizontal gene transfer (HGT) and we assume that the species tree is unknown. Although many problems become NP-hard as soon as HGT and time-consistency are involved, we show, in contrast, that the problem of finding a time-consistent species tree for a given event-labeled gene can be solved in polynomial-time. We provide a cubic-time algorithm to decide whether a “time-consistent” species tree for a given event-labeled gene tree exists and, in the affirmative case, to construct the species tree within the same time-complexity

Network Biology Approaches to Identify Molecular and Systems-Level Differences Between Salmonella Pathovars

The field of systems biology endeavors to map, study, and simulate cellular systems and their underlying mechanisms. The internal mechanisms of biological systems can be represented with networks comprising nodes and edges. Nodes denote the constituents of the biological system whereas edges indicate the relationships among them. Likewise, every layer of cellular organization can be represented by networks. Multilayered networks capture interactions between various network types, such as transcriptional regulatory networks, protein–protein interaction networks, and metabolic networks from the same biological system. This property makes multilayered networks representative of the system while its internal mechanisms are investigated. However, there are not many multilayered networks containing integrated data for nonmodel organisms including the bacterial pathogens Salmonella. Here, we outline the steps to create such an integrated network database, through the example of SalmoNet, the first integrated multilayered data resource for multiple strains belonging to distinct Salmonella serovars