Using isotopic envelopes and neural decision tree-based in silico fractionation for biomolecule classification.

Untargeted mass spectrometry (MS) workflows are more suitable than targeted workflows for high throughput characterization of complex biological samples. However, analysis workflows for untargeted methods are inadequate for characterization of complex samples that contain multiple classes of compounds as each chemical class might require a different type of data processing approach. To increase the feasibility of analyzing MS data for multi-class/component complex mixtures (i.

Characterization of Electrospray Ionization (ESI) Parameters on In-ESI Hydrogen/Deuterium Exchange of Carbohydrate-Metal Ion Adducts.

The conformations of glycans are crucial for their biological functions. In-electrospray ionization (ESI) hydrogen/deuterium exchange-mass spectrometry (HDX-MS) is a promising technique for studying carbohydrate conformations since rapidly exchanging functional groups, e.g.

Improving Accuracy and Confidence of Chemical Identification by Gas Chromatography/Vacuum Ultraviolet Spectroscopy-Mass Spectrometry: Parallel Gas Chromatography, Vacuum Ultraviolet, and Mass Spectrometry Library Searches.

Chemical identification often relies on matching measured chemical properties and/or spectral "fingerprints" of unknowns against their precompiled libraries. Chromatography, absorption spectroscopy, and mass spectrometry are all among analytical approaches that provide chemical measurement databases amenable to library searching. Occasionally, using conventional single-library or single-domain searches can lead to misidentification of unknowns.

Broadband ion mobility deconvolution for rapid analysis of complex mixtures.

High resolving power ion mobility (IM) allows for accurate characterization of complex mixtures in high-throughput IM mass spectrometry (IM-MS) experiments. We previously demonstrated that pure component IM-MS data can be extracted from IM unresolved post-IM/collision-induced dissociation (CID) MS data using automated ion mobility deconvolution (AIMD) software [Matthew Brantley, Behrooz Zekavat, Brett Harper, Rachel Mason, and Touradj Solouki, J. Am.

Vacuum Ultraviolet Spectroscopy and Mass Spectrometry: A Tandem Detection Approach for Improved Identification of Gas Chromatography-Eluting Compounds.

For wide class characterizations of volatile organic compounds (VOCs), conventional gas chromatography mass spectrometry (GC-MS)-based techniques are utilized. These GC-MS-based chemical identification approaches typically rely on library searches against ion fragmentation patterns of known compounds. Although MS library searches can often provide correct chemical identities, erroneous chemical assignments of structurally similar unknown compounds are also possible.

Automated peak width measurements for targeted analysis of ion mobility unresolved species.

Peak broadening in ion mobility (IM) is a relatively predictable process and abnormally broad peaks can be indicative of the presence of unresolved species. Here, we introduce a new ion mobility peak fitting (IM_FIT) software package for automated and systematic determination of traveling wave ion mobility (TWIM) unresolved species. To identify IM unresolved species, the IM_FIT software generates a trend line by plotting ions' mobility peak widths as a function of their arrival times.

Collision-energy resolved ion mobility characterization of isomeric mixtures.

Existing instrumental resolving power limitations in ion mobility spectrometry (IMS) often restrict adequate characterization of unresolved or co-eluting chemical isomers. Recently, we introduced a novel chemometric deconvolution approach that utilized post-IM collision-induced dissociation (CID) mass spectrometry (MS) data to extract "pure" IM profiles and construct CID mass spectra of individual components from a mixture containing two IM-overlapped components [J. Am.