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The annotations were performed using the FEELTRACE [77] emotion annotation tool.
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Most of the annotation was performed using precalculated annotations from the Saccharomyces Genome Database [ 61].
The annotation was performed using the software GOTM (Gene Ontology Tree Machine) that also compare the frequency of genes in each functional class with the expected frequency based on the distribution of all human genes throughout the GO functional classes.
The annotation was performed using Geneious 6.0 to identify the open reading frames (ORFs) that started with a methionine codon (ATG) encoding at least 50 amino acids and blastp [ 63] to identify homologues.
The β-keratin annotations were performed using the standalone BLAST+ program and the Greenwold and Sawyer [ 9] dataset as a database.
The GO and KEGG pathway functional annotations were performed using the FatiGO+ tool of the Babelomics suite [27].
The Gene ontology (GO) and KEGG pathway functional annotations were performed using the NIH web-based tool DAVID (the Database for Annotation, Visualization and Integrated Discovery; Huang da et al. 2009).
The GO and KEGG pathway functional annotations were performed using the National Institutes of Health web-based tool DAVID (Database for Annotation, Visualization and Integrated Discovery) [ 69].
KEGG pathways annotations were performed using the KEGG Automatic Annotation Server (KAAS) with the bi-directional best-hit information method [ 27].
InterPro annotations were performed using the Blast2GO remote connection to the InterProEBI server [ 48].
Functional annotations were performed using the Gene Ontology (http://www.geneontology.org/).org/
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