Resolution:
## Figure 6.
Example of sequential patterns. Example: (a) an expression matrix, ∈ ℜE^{|}^{G}^{|×|}^{S}^{|} where || = 11 and |G| = 7, (b) a sequence database, S, and (c) the set of sequential patterns, D, identified by each of the three cases. The search parameters are set to P = 5, u = 2, l = 4, and w_{f} = 2. is the summary set eliminating trivial patterns which are enclosed by other patterns.
Compared with Case 1, Case 3 searches long sequential patterns. All the patterns found
from Case 1 have the length of 2 or 3 (|w_{b}| = 2 or |p_{g}| = 3), whereas 27 out of the 43 patterns found from Case 3 have longer length than
3 (|p_{g}| ≥ 3). Note that the longer patterns are more likely to have biological implication
than the shorter ones which can be found by chance. Compared with Case 2, Case 3 shows
the effect of backward lookup. By allowing trivial switch between consecutive elements
in a sequence, one can still identify sequential patterns despite innate noise in
data, e.g., experimental noises in a microarray matrix.
p_{g}Kim |