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Regulated genes were associated with biological functions using previously published literature reports and various databases, in addition to upstream and downstream regulation analysis and canonical pathway analysis generated by Ingenuity Pathway Analysis (IPA) software.
The H class was further characterized (again based on similarities to various databases, in particular the KOG and Gene Ontology databases) into 21 functional groups (Table 2), the unknown conserved class being the most prevalent [ 32].
After browsing the entries of these databases, a brief introduction to the commonly used databases and the differences among these databases is given, so that the students can have a general overview of various databases in bioinformatics.
While these 3 parameters have been already part of many HSQC databases, they are often not sufficiently selective to reliably discriminate between true and false identifications (see false positive rates of various databases in the results section).
From a biologists point of view, PsicquicGraph and the BioJS initiative are extremely positive as it will allow for the retrieval of information from various databases in a seamless manner.
The H class was further characterized (again based on similarities to various databases, in particular the KOG and Gene Ontology [GO] databases) into 20 functional groups (Table 1), the unknown conserved class being the most prevalent [ 19].
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Predicted genes were functionally annotated based on homology to annotated genes in various databases via BLAST.
Tables 1 and 2 summarize the percentages of mispredicted sequences in various databases and in 19 metazoan species.
It also includes any imperfection in the various databases used in GUPIX [ 16, 17].
The total number and percentage of reads aligning to the various databases used in this study are provided in the Additional file 11: Table S9 and Additional file 12: Table S10.
Proteomes of freely available fungal pathogens were sourced from various databases listed in Table 1.
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