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The number of overlapping points between frames is calculated as follows: Overlap = 512 - fs/ stimulation rate).
For an active pathway (AP) and a database pathway (DP) pair, we define a similarity score: score AP, DP = overlap AP, DP pvalu e AP + pvalu e DP, where the overlap in the numerator is defined as follows, overlap AP, DP = number of genes in AP and in DP number of genes in AP.
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It can be calculated as follows: Overlapping percentage = s g1 + g2 - s × 100%%.
In what follows, overlaps between lists are reported if and only if such overlaps reached statistical significance.
Following, overlapping or identical clusters, in the case of isoforms through alternative splicing, had to be resolved.
Parameters were set as follows: (i) overlap percent identity cutoff was 95%, (ii) overlap length cutoff was 49, and (iii) maximum number of word matches was 10,000 (this parameter defines the maximum number of matches that the program will consider for a given sequence, and was set high to improve accuracy [ 46].
The expectation of ∼165 overlaps in the absence of sex-specific effects was calculated as follows: expected overlap = (number of significant transcript/marker pairs)* [fraction true positives]*[power]+[fraction false positives]*[overlap between false positives]).
Finally, the output speech sout(n) can be represented as follows by overlap addition of the preprocessing speech frames: {s}_{mathrm{out}}(n)=sum limits_{m=1}^p{y}_m(n). (11).
The protocols of our SSOE-PCR are as follows: First, overlap primers containing two parts of sequences respectively matching with DNA1 and DNA2 must be designed and then two longer DNAs with overlap sequences are amplified by normal PCR program.
In order to present an adequate source for reference sequencing and avoid such gaps at the sequence level, clone overlaps marked as 'unreliable' by LTC is reinforced with additional clones, as follows: For overlaps that were significant only at a cut-off of 10−14 or above, 210 additional clones covering the same overlap were picked manually.
We can capture much of the information in a reference transcriptome using a graph G that has a node for every kmer that occurs in a transcript and an edge (u, v) between any two kmers u and v if v follows u, overlapping it by k − 1 characters, in some transcript.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com