| Literature DB >> 23193296 |
Aaron David Goldman1, Tess M Bernhard, Egor Dolzhenko, Laura F Landweber.
Abstract
Organisms represented by the root of the universal evolutionary tree were most likely complex cells with a sophisticated protein translation system and a DNA genome encoding hundreds of genes. The growth of bioinformatics data from taxonomically diverse organisms has made it possible to infer the likely properties of early life in greater detail. Here we present LUCApedia, (http://eeb.princeton.edu/lucapedia), a unified framework for simultaneously evaluating multiple data sets related to the Last Universal Common Ancestor (LUCA) and its predecessors. This unification is achieved by mapping eleven such data sets onto UniProt, KEGG and BioCyc IDs. LUCApedia may be used to rapidly acquire evidence that a certain gene or set of genes is ancient, to examine the early evolution of metabolic pathways, or to test specific hypotheses related to ancient life by corroborating them against the rest of the database.Entities:
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Year: 2012 PMID: 23193296 PMCID: PMC3531223 DOI: 10.1093/nar/gks1217
Source DB: PubMed Journal: Nucleic Acids Res ISSN: 0305-1048 Impact factor: 16.971
Figure 1.An overview of methods used to map the eleven early life data sets onto the underlying database framework of Uniprot, KEGG and Biocyc IDs. Initial data sets extracted either from previous studies or generated by the authors are highlighted in blue. Line thickness corresponds directly to the number of files at each methodological step. A complete description of ID mapping for each data set can be found in the LUCApedia documentation available for download from the web server.
Figure 2.A screen shot of the LUCApedia web server search function. Protein names can be entered into the search field and the search will return all corresponding Uniprot IDs along with evidence of their relevance to ancient life. Searches may be conducted for either exact or partial protein names. If a name search does not return any results, Uniprot IDs may also be directly queried.