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Nucleotide sequences of 12 405 pairs of orthologous coding regions of human and mouse were extracted from the Searchable Prototype Experimental Evolutionary Database (SPEED) (http://www.bioinfobase.umkc.edu/speed/), using an in-house program developed in Perl.
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To identify overrepresented categories of genes, we inputted the overexpressed RefSeq genes into the PANTHER (Protein Analysis Through Evolutionary Relations) database (http://panther.appliedbiosystems.com) and compared them to a human reference list of transcribed genes [52].
To address this gap, EvoDB (an Evolutionary rates DataBase) was compiled.
The gene-ontology terms used are those of the PANTHER (Protein ANalysis THrough Evolutionary Relationships) database.
To address this gap in knowledge, EvoDB (an Evolutionary rates DataBase) was compiled.
In this paper, the PANTHER (Protein ANalysis THrough Evolutionary Relationships) database [ 20] and its corresponding scanning tools, BLAST and hmmsearch, are used within InterProScan.
Functional grouping of the gene list into statistically significant overrepresented ontologies was performed using the protein analysis through evolutionary relationships database analysis tools (PANTHER).
For figure 1 please see additional files 1, 2, 3, 4, for figure 2, please see additional files 5, 6, 7, 8. SAM identified transcripts were loaded into the PANTHER (Protein ANalysis THrough Evolutionary Relationships) database.
To determine which biological processes were represented by the differences in gene-expression levels for each comparison (early versus LS RA; early RA or LS RA versus controls), we applied gene-ontology analysis using the PANTHER (Protein ANalysis THrough Evolutionary Relationships) database [ 13- 15].
Nevertheless, evolutionary-based databases have higher coverage of domains than structure-based databases [ 14, 25].
Since our domains represent structurally compact evolutionary units, the database may be useful for studying domain properties and evolution.
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