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Note the number of candidate sequences that pass the filter cascade.
Compared to the low passing rates we observed for LG-B and LG-T candidate sequences that pass filter step 4 in P-ER2, majofitheof the candidate sequences generated by multiSrch in the P-ERM protocol (for both LG-B and LG-T) pass filter step 4.
For LG-B logic operators, (cf. Table 8), one can observe a significant improvement in the number of candidate sequences that pass the filtering procedure (indicated by percentage of passing in column Rate in Table 8) when compared to the P-ER2 protocol.
Only those sequences that pass five quality filters are present in the final data set.
Then for cDNA sequences that pass these filters, we kept the UniGene ACC corresponding to the sequence with the best score for each species to annotate the corresponding clone.
The resulting list of sequence windows is appropriate for scoring under the medium-precision filter; those sequences that pass a pre-defined threshold are further passed to the high-precision final alignment.
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The percentage of sequences that passed the cascade is listed in the success rate column.
The columns (T1 to T10) represent the number of candidate sequences that passed the seven filter cascades in Table 4.
A design for a molecular XOR gate was selected to illustrate its operation from the pool of candidate sequences that passed all the filter stages in Table 4.
Table 4 P scores for various image sequences using Chan-Vese energy as classification criteria Sequence P score Classification (pass/fail) 2 6.9316 Pass 6 0.4642 Fail 7 4.2569 Pass 10 13.1468 Pass Table 5 Segmentation results from image sequences that passed level set filtering Sequence Dice's coefficient 2 0.8698 7 0.6113 20 0.6667.
Sequences that passed trimming were assembled by Velvet [53].
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Justyna Jupowicz-Kozak
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