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. 2010 Mar 22;11:146. doi: 10.1186/1471-2105-11-146

Table 1.

Sequence and structural alignment scores for two example alignments.

Levitt-Gerstein Structural Similarity Sequence Alignment Score Shift Score vs. Dali Levitt-Gerstein Structural Similarity Sequence Alignment Score Shift Score vs. Dali
Alignment 1 hdaB00 vs. 1 mytA00 (pair 25) 1bcgA00 vs. 1b7dA00 (pair 42)

CE 2333 85 0.986 978 61 0.920
Matras 2330 103 0.983 966 49 -
DALI 2334 115 1.000 980 24 1.000
LSQMAN 2337 -20 0.946 980 24 0.940
Optimal Sequence§ 2352 145 0.940 583 108 0.837
95% Neighborhood§ 2355 145 0.900 696 104 0.880
75% Neighborhood§ 2359 145 0.923 812 88 0.780
probA§ 2362 37 0.645 830 37 0.757
robustness 2301 -526 0.734 383 24 0.565
model 2352 145 0.941 579 108 0.796

Semi-global alignment, Blosum50 substitution matrix, gap open penalty -10, gap extension penalty -2.

§ The sequence with the highest Levitt-Gerstein similarity score was chosen from the set of optimal alignments, the set of alignments with a sequence similarity score within 95% of optimal, the set of alignments with a sequence similarity score within 75% of optimal, and the set of probA alignments, and the sequence similarity score and shift score for that alignment were recorded.

Alignments were created using the log-odds score produced by a logistic regression model in place of a substitution matrix. "Robustness" refers to a model that had only robustness as an independent variable, while "model" refers to the full model (incorporating robustness, edge frequency, and maximum bits-per-position). See text for details.