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To exclude the possibility of drug resistance mutations impacting on the entropy calculations, epitopes containing amino acid positions known to acquire mutations causing high, intermediate or low level resistance to RT and protease inhibitors (Stanford University Drug Resistance database) were removed from the list of epitopes and all the calculations were repeated.
Those ORFs with a top BLAST hit to a non-methanogen or with no homology to the nr database were removed from the analysis, as were transposase sequences (which are unlikely to represent good vaccine targets), while adhesin-like ORFs are dealt with separately above.
Duplicate articles within each database were removed, leaving 446 articles.
Further sequences matching non-coding rRNA, tRNA, snRNA and snoRNA in the Rfam database were removed.
Sequences matching noncoding rRNA, tRNA, snRNA and snoRNA in the Rfam database were removed.
To avoid redundant miRNAs, duplicated miRNAs shared between different species within the database were removed.
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Finally, any predicted protein whose sequence was either a subsequence or an identical duplicate of one entry in the RefSeq database was removed before conducting the database searches.
To further investigate the influence of this factor, we have performed two different tests: a deletion experiment, in which a percentage of the database is removed to simulate a reduction in our current knowledge, and a test of assignment involving sequences from rare taxa, which probably represent the most serious challenge to the method.
Identical compounds found in both ACD and MDDR databases were removed from ACD.
The spreadsheets for each SSU processome protein were merged into a master file and duplicate entries originating from PPIs listed in both BioGRID and IntAct databases were removed (Table S2).
Identical sequences, such as those obtained from both Uniref90 and Uniref50 databases, were removed from further analysis.
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