Peptide sequences for applied peptides were confirmed with mass spectrometry by the peptide company (Chinese Peptide Company, Beijing, China) after synthesis.
The analysis was performed in a two-step classification procedure, involving automatic prediction and classification in silico, combined with manual curation for each of the protein groups, virtually sequence for sequence applying systematic comparisons with a range of databases and other resources.
On the one hand, the success of classification methods using fairly simple low-level features of protein sequence offer hopeful indications for applying this sort of approach to analysis of clinical samples for the prognosis, diagnosis or stratification of patients in the context of both infectious and non-infectious (e.g. cancer, autoimmunity or transplantation) disease.
Most importantly, the data obtained (SNPs or 30 200-bp sequences) are not appropriate for applying phylogenetic approaches that estimate species trees from a large number of gene trees.
With the increased genomic sequences available, the capacity for applying phylogenetic analysis methods has increased; however, there is urgent need to evaluate their equivalency.
This may even hold for applying Sanger sequencing for validation purposes, although this aspect was not considered in our study.
Finally, we calculated phylogenetic trees for all sequence sets by applying Maximum Likelihood (Felsenstein, 1981) to the Clustal W multiple alignments.
As BAliBASE contains no information about the underlying phylogenetic trees, we constructed a reference tree for each sequence set by applying the standard Maximum Likelihood method (Felsenstein, 1981) to the corresponding reference multiple alignment.
We can design an equivalent for sequence data: for each sequence, apply some random number of possible mutations under a chosen model, then estimate all pairwise distances under the same model, and finally subtract from that estimate the number of mutations applied in the perturbation step to each of the two sequences a method we denote BP.
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The numbers in parentheses refer to the standard deviation of, respectively, the mean r s, o and the mean v ̄ s across the ten synthesized dance sequences for each applied parameterization.
