Sentence examples for a mass error from inspiring English sources

Positive identifications of fungal metabolites were reported if the compound was detected with a mass error below 10 ppm and with a sufficient score.

Precursors were filtered according to charge state (2 6 z) and monoisotopic peak assignment, and previously selected peaks were excluded using a dynamic window of 60 s with a mass error ±10 ppm.

Searches were performed allowing for complete carbamidomethylation (alkylation) of cysteine residues, partial oxidation of methionine residues, one missed cleavage and a mass error of 250 ppm.

Mass spectral peaks were detected between 50 and 1000 m/z with a mass error window of 0.07 m/z, and the de-isotoping function was enabled.

The Expasy FindPept tool analysis revealed that this corresponds to a peptide from CXCL9 spanning amino acids 18 to 73 with a mass error of 0.03 Da (Fig. 4B).

For the LTQ-Orbitrap Velos data, the distribution of mass deviation (from the theoretical masses) was first determined as having a standard deviation of 2.05 part per million (ppm), and a mass error of smaller than 3σ was used in combination with Xcorr and ΔCn to determine the filtering criteria that resulted in <1% false positive peptide identifications.

Proteome Discoverer was used with a monoisotopic mass selected, a precursor mass error of 25 ppm, and a fragment ion mass error of 0.8 Da.

The relevant search parameters were as follows: enzyme specificity was fully tryptic, a precursor mass error of 3.0 Da, a fragment mass error of 0.5 m/z, and a peptide mass range spanning 400 to 5100 Da.

A parent mass error of up to 10 ppm was allowed for the searches, and a product mass error of 0.4 Daltons.

Precursors with a recalibrated mass error greater than 10 ppm were discarded.

For modified precursor peptides displaying a ppm mass error less than 10, MS/MS spectra were interrogated with Xcalibur software.