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This is why it's so important that human biometrics experts make the final determination as to whether a match is correct, he says.
where d = − |MLPA 1 − MLPA 2|, c = 1 2 FSP C 1 + FSP C 2. d is the similarity component that reflects how well the two signals resemble each other, and c is the confidence component that reflects the confidence that a match is correct.
This makes it necessary to have certainty that the match is correct.
In addition, Riptide can be used to produce likelihood scores that indicate whether a given peptide-spectrum match is correct.
It is important to note that in this case, the adversary cannot know if this match is correct or not, s/he only knows the probability of the match being correct.
Therefore, it is important for any tool to provide users with a reliable false discovery rate (FDR), which is the measure of probability that a match is correct, based on the program's performance in analyzing the entire data set.
Similar(54)
We considered that a match was correct if its disparity error with the ground truth was smaller than the 2D primitives' size — this ensures that no erroneous match is considered as correct.
An adversary can contact neighbourhood businesses and individuals, and directly call potential matches to verify if a match was correct.
For example, if the value of P is 1, then the adversary is always able to verify if a match was correct or not.
The probability that a match was correct (P <0.05) was determined using the Mascot derived ion score where P was the probability that the observed match was a random event.
For a fixation line, the difference between the best matching score s 1 and the second best matching score s 2 is computed: D=s 1−s 2. If this difference is large enough (D>T), we consider that the matching is correct.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com