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QuePED provides for the performance modelling of database design constructs, including active database rules; thus, deviating from current methods that consider database designs as processing demands on the hardware architecture.
Using non-uniform strides would make the preprocessing take longer, but we do not consider database preprocessing time as a primary measure of performance, since preprocessing is done outside MegaBLAST.
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The rest of this paper considers database ({mathcal {T}}) shown in Fig. 1a.
More recently, a few works have considered database replication under byzantine failures (e.g., [20, 23]).
where indexes each sequence of LSF vectors of the considered database, M being the number of sequences.
During database search the following parameters were considered: database, NCBInr; maximum missed cleavages, 1; precursor tolerance, 0.2 Da; peptide charges, +1; mass, monoisotopic.
This construction is independent from a considered database and the probability will usually be very similar.
Consensus motifs can also be used instead of existing PWM and the considered database should be well populated with TFBS of interest.
We also see that the error of the estimated abundances is low for all considered database sizes and only increases slightly with the number of proteomes.
Analysis of the Inr positional distribution for the considered database (see Additional file 1, Supplemental Figure S3c) shows significant over-representation for the Inr motif in the area (-1 to +9 bp).
For both scenarios and for all considered databases, the process of database construction have been done in the same way.
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