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Qualitative identification was performed using GC MS reference libraries (Adams [ 17], Wiley 7th, and NIST 2.0) using a 80% similarity match cut off value.
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It is possible that those who did not see the information on the crawl felt that the match was cut off well before its finish.
Peak identity was established by comparison of the fragmentation pattern with MS publicly available databases (NIST), using a match cut-off criterion of 750/1000 and by RI using the alkane series as standards.
Potential transcription factor binding sites in the human MER20-derived decidual PRL enhancer (dPRL) were identified using the MATCH program (http://.gene-regulation.com/) utilizing TRANSFAC binding site matrices with a match cut-off selected to minimize the sum of false positive and false negative results.
Four different match cut-off values for FACS were evaluated when using the mitochondrial reference (Supplementary Fig. 1).
Different match cut-off values were used with MEGABLAST to evaluate the reads classified with each method (Supplementary Fig. 2).
Four different match cut-off values for FACS were evaluated when using the human reference (Supplementary Fig. 3).
A sequence similarity of 45% with an alignment spanning over at least 45% of the query length served as a match cut-off for correct classification.
These homolog sequences accounted for <0.056% of all classified reads in the four K-mer sets with the different FACS match cut-off values.
As expected, increasing the size of the K-mer and the match cut-off resulted in fewer classified reads and fewer false positives.
A K-mer size of 21 bases while using 35 80% sequence identity match cut-off resulted in 100% specificity and no false positives.
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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