The classic evolutionary tree is challenged in the face of new genomic data. Using mathematical and computational tools, the more complex phylogenetic network is better suited to accurately represent complex evolutionary relationships.
Phylogenetics uses a tree to depict the evolutionary links between groups of species. However, an evolutionary tree cannot adequately represent all genetic processes occurring throughout evolution. The use of different genetic loci, for example, will give conflicting species interrelationships due to processes such as horizontal gene transfer and recombination.
The LIFENET (New algorithmic and mathematical tools to construct a net of life) project has developed algorithms to construct phylogenetic networks. The team studied gene recombination events in viruses to provide new insight into evolution of viruses such as HIV.
The research group has established an algorithm to quantify hybridisation for an arbitrary number of trees that was previously limited to two trees. Furthermore, parsimony analyses for trees were extended to networks. Previously used parsimony frameworks produce networks with reduced biological relevance. LIFENET has therefore proposed a new definition of parsimony for networks.
LIFENET also settled questions related to the computational complexity of several decision problems related to phylogenetic networks. For example, it was shown that counting the number of trees that a phylogenetic network simultaneously embeds is a computationally hard problem.
Research results have been published in several peer-reviewed journals. The work also helped to establish fruitful collaborations between researchers in Germany, the Netherlands, New Zealand and the United States.
LIFENET has enabled the incorporation of a variety of genetic events into a phylogenetic network or tree. Complex interactions are common through evolution and their incorporation is necessary for the application of disease therapy.
EN 
CS
DE
ES
FR
HU
IT
PL
PT
РУ
SK
TR
УК
AR
中文
