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The TM-score indicates the similarity between two structures by a score between (,], where 1 indicates a perfect match between two structures (thus the higher the better). [1] Generally scores below 0.20 corresponds to randomly chosen unrelated proteins whereas structures with a score higher than 0.5 assume roughly the same fold. [2]
TM-score – a different structure comparison measure; Longest continuous segment (LCS) — A different structure comparison measure; Global distance calculation (GDC_sc, GDC_all) — Structure comparison measures that use full-model information (not just α-carbon) to assess similarity
The score is greater than 0 if it is more likely to be a functional site than a random site, and less than 0 if it is more likely to be a random site than a functional site. [1] The sequence score can also be interpreted in a physical framework as the binding energy for that sequence.
By the original design the GDT algorithm calculates 20 GDT scores, i.e. for each of 20 consecutive distance cutoffs (0.5 Å, 1.0 Å, 1.5 Å, ... 10.0 Å). [2] For structure similarity assessment it is intended to use the GDT scores from several cutoff distances, and scores generally increase with increasing cutoff.
In statistics, probability theory and information theory, pointwise mutual information (PMI), [1] or point mutual information, is a measure of association. It compares the probability of two events occurring together to what this probability would be if the events were independent. [2]
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The pairing of G and G is a match, so add the score for match: 0+1 = 1; The top neighbor has score −1 and moving from there represents an indel, so add the score for indel: (−1) + (−1) = (−2) The left neighbor also has score −1, represents an indel and also produces (−2). The highest candidate is 1 and is entered into the cell:
If the null hypothesis is true, the likelihood ratio test, the Wald test, and the Score test are asymptotically equivalent tests of hypotheses. [8] [9] When testing nested models, the statistics for each test then converge to a Chi-squared distribution with degrees of freedom equal to the difference in degrees of freedom in the two models. If ...