BioVeL supports scientists to carry out research on biodiversity by offering computerized tools ("workflows") to process large amounts of data from your own and cross-disciplinary sources, as well as tools for designing and running workflows. The BioVeL phylogenetic service set allows performing phylogenetic inferences for systematics research. Sev ...
DOI: 10.22323/1.162.0029
Last Update: 2018
Data analysis Genetic composition
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BioVeL supports scientists to carry out research on biodiversity by offering computerized tools ("workflows") to process large amounts of data from your own and cross-disciplinary sources, as well as tools for designing and running workflows. The BioVeL phylogenetic service set allows performing phylogenetic inferences for systematics research. Several services offer Bayesian methods to guide the selection of the evolutionary model and performing a post hoc validation of the inference. The set further includes the phylogenetic partitioning of the diversity across samples, allowing the study of mutual information between phylogeny and environmental variables. Other services provide an integrated solution to the phylogenetic inference of large time calibrated trees (SUPERSMART services). To this end, public data resources are mined for suitable molecular sequence data, which is subsequently processed to form a starting point for phylogenetic inference using Bayesian and Maximum-Likelihood methods. Inferred trees can then be time-calibrated using fossil data. Furthermore, services for the enrichment and conversion of data resources in standard data formats for phylogenetic analysis are available (nexml service set). These services can be integrated into phylogenetic inference workflows. BioVeL is funded by the EU’s Seventh Framework Program, grant no. 283359.
Contact person: | Alex Hardisty |
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Contact e-mail: | hardistyar@cardiff.ac.uk |
Contact Organization: | Cardiff University, UK |
URL(s): | https://www.academia.edu/20705177/The_BioVel_Project_Robust_phylogenetic_workflows_running_on_the_GRID |
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