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Saptarshi Biswas

Profile photo of Saptarshi Biswas
PhD Students
PhD Student
Area of Expertise: 
Theory of Computation
Molecular Memory (Nucleic Acid Memory)
Machine Learning/Deep Learning Optimization

Oliver Eulenstein

Oliver Eulenstein
Faculty
Professor
Area of Expertise: 
Computational Biology
Bioinformatics
Combinatorial Optimization

Computational Biology Laboratory

Supertrees are phylogenies (rooted evolutionary trees) assembled from smaller phylogenies that share some but not necessarily all taxa (leaf nodes) in common. Thus, supertrees can make novel statements about relationships of taxa that do not co-occur on any single input tree while still retaining hierarchical information from the input trees. As a method of combining existing phylogenetic information, supertrees potentially solve many of the problems associated with other methods (e.g., absence of homologous characters, incompatible data types, or non-overlapping sets of taxa). In addition to helping synthesize hypotheses of relationships among larger sets of taxa, supertrees can suggest optimal strategies for taxon sampling (either for future supertree construction or for experimental design issues such as choice of outgroups), can reveal emerging patterns in the large knowledge base of phylogenies currently in the literature, and can provide useful tools for comparative biologists who frequently have information about variation across much broader sets of taxa than those found in any one tree. This web site brings together information and tools to assist phylogenetic biologists and others interested in using supertrees in their research or teaching. It provides background information on the theory and links to examples with real data. It also provides a venue for archiving of software tools for supertree construction as they become available, as well as links to other efforts in this area.

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