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In this study, the Swissprot, MSDB, NCBInr, Random databases, MASCOT, and MS-Fit were selected as search engines, and the standard CAH2_BOVIN was used as model to set up protein search standard conditions.
Since the biological database is not a collection of random peptides, the validity of statistical theory founded on random databases should be tested.
Database searches were performed against normal and random databases using the following parameters: full tryptic enzymatic cleavage with three possible missed cleavages, peptide tolerance of 1,000 ppm, fragment ion tolerance of 0.6 Da, and variable carboxyamidomethylation (+57 Da) modification.
The conditional spectral probabilities estimated using the new random databases are different from those using the random databases in Subsection "Computation of correct conditional spectral probabilities" because the protein sequences in the new random databases are not independent.
This relatively minimal effect may be due to the phylogenetic diversity already present in random databases.
Since the random databases contain no true positives, all hits found were false positives.
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Several features on Amazon.com, like the list of authors with books similar to the one being viewed, take what could be a random database and develop relationships within it.
It would be recommended to utilize independent search combining random database with statistics theorem to estimate the accurate FDR of the identified results.
A second decoy (random) database was constructed by reversing sequences from the normal database.
The data described by Fjell et al. [19] (named RANDOM database) on different antimicrobial peptides was also independently used to test the method.
We have also inspected the database (named RANDOM database) described recently by Fjell et al. [19] that contents a set of 189 peptides randomly synthesized and experimentally tested, again in uniform conditions.
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