
Comparative genomics promises to rapidly accelerate the identification and functional classification of biologically important human genes. We developed the TIGR Orthologous Gene Alignment (TOGA; 〈http://www.tigr.org/tdb/toga/toga.shtml〉) database to provide a cross-reference between fully and partially sequenced eukaryotic transcribed sequences. Starting with the assembled expressed sequence tag (EST) and gene sequences that comprise the 28 TIGR Gene Indices, we used high-stringency pair-wise sequence searches and a reflexive, transitive closure process to associate sequence-specific best hits, generating 32,652 tentative ortholog groups (TOGs). This has allowed us to identify putative orthologs and paralogs for known genes, as well as those that exist only as uncharacterized ESTs and to provide links to additional information including genome sequence and mapping data. TOGA provides an important new resource for the analysis of gene function in eukaryotes. In addition, an analysis of the most widely represented sequences can begin to provide insight into eukaryotic biological processes.
Genome, Human, Computational Biology, Rats, Mice, Eukaryotic Cells, Genes, Sequence Homology, Nucleic Acid, Consensus Sequence, Databases, Genetic, Animals, Humans, Cattle, Sequence Alignment, Algorithms, Phylogeny
Genome, Human, Computational Biology, Rats, Mice, Eukaryotic Cells, Genes, Sequence Homology, Nucleic Acid, Consensus Sequence, Databases, Genetic, Animals, Humans, Cattle, Sequence Alignment, Algorithms, Phylogeny
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