Sentence examples for molecular formulas to from inspiring English sources

Rogers et al[152] used a similar approach on molecular formula level to assign better molecular formulas to metabolites (see Section "Other approaches for molecular formula identification").

More restrictive filtering such as the Seven Golden Rules [20] (orange) further reduce the number of molecular formulas to be considered; nevertheless, multiple explanations remain for most precursor ions.

If we want to assign molecular formulas to the precursor and product ions, we may use the formula of the precursor to filter bogus explanations of the product ions, and vice versa.

The proposed model simultaneously groups related peaks and assigns molecular formulas to the groups.

Nevertheless, for all analyzed unknown metabolites, FragExtract performed a spectral cleanup and restricted the number of possible molecular formulas to one or two possibilities.

We assume that we can identify the correct molecular formula from the data: limiting candidate molecular formulas to those present in KEGG (Kanehisa and Goto, 2000), which is used for searching molecular structures below, the best scoring fragmentation tree identified the correct molecular formula of the compound in 97.1% (96.0%) of the cases for the METLIN (MassBank) dataset.

We currently use the Chemical Development Kit [4] to compare the molecular weight generated from the molecular formula to the molecular weight generated from the structure.

The HRESIMS established the molecular formula to be C17H24O2 on the basis of a molecular ion peak at m/z 259.1704 (calcd for C17H23O2: 259.1704 [M − H]−).

Here, both the intensities and masses of the isotope pattern are used to score candidate molecular formulas using Bayesian statistics: The authors estimate the likelihood of a particular molecular formula to produce the observed data.

FTs annotate the MS/MS spectra and also model the fragmentation processes that generated the fragment ions: each node in the FT assigns a molecular formula to a fragment peak, whereas edges represent fragmentation reactions and are labeled with the molecular formula of the corresponding loss.

The collection of workflows are defined as PUTMEDID_LCMS and perform feature annotation, matching of accurate m/ z to the accurate mass of neutral molecules and associated molecular formula and matching of the molecular formulae to a reference file of metabolites.