A New Library-Search Algorithm for Mixture Analysis Using DART-MS

2021 ◽  
Author(s):  
Arun S. Moorthy ◽  
Edward Sisco
Keyword(s):  
Search Algorithm ◽  
Mixture Analysis ◽  
Library Search

scholarly journals A New Library-Search Algorithm for Mixture Analysis Using DART-MS

2021 ◽  
Author(s):  
Arun Moorthy ◽  
Edward Sisco
Keyword(s):  
Mass Spectrum ◽  
Mass Spectra ◽  
Search Algorithm ◽  
Collision Induced Dissociation ◽  
Two Stage ◽  
Library Search ◽  
Prototype Implementation ◽  
Search Results ◽  
Protonated Molecules ◽  
Acetyl Fentanyl

This manuscript introduces a new library-search algorithm for identifying components of a mixture using in-source collision-induced dissociation (is-CID) mass spectra. The two-stage search, titled the Inverted Library-Search Algorithm (ILSA), identifies potential components in a mixture by first searching its low fragmentation mass spectrum for target peaks, assuming these peaks are protonated molecules, and then scoring each target peak with possible library matches using one of two schemes. Utility of the ILSA is demonstrated through several example searches of model mixtures of acetyl fentanyl, benzyl fentanyl, amphetamine and methamphetamine searched against a small library of select compounds and the NIST DART-MS Forensics library. Discussion of the search results and several open areas of research to further extend the method are provided. A prototype implementation of the ILSA is available at <a href="https://github.com/asm3-nist/DART-MS-DST">https://github.com/asm3-nist/DART-MS-DST</a>.

Pattern Recognition-Assisted Infrared Library Searching of the Paint Data Query Database to Enhance Lead Information from Automotive Paint Trace Evidence

2016 ◽  
Vol 71 (3) ◽  
pp. 480-495 ◽  
Author(s):  
Barry K. Lavine ◽  
Collin G. White ◽  
Matthew D. Allen ◽  
Andrew Weakley
Keyword(s):  
Pattern Recognition ◽  
Ir Spectra ◽  
Search Algorithm ◽  
Paint Layer ◽  
Trace Evidence ◽  
Discrimination Power ◽  
Library Search ◽  
Layer Sequence ◽  
Data Query ◽  
Automotive Paint

Multilayered automotive paint fragments, which are one of the most complex materials encountered in the forensic science laboratory, provide crucial links in criminal investigations and prosecutions. To determine the origin of these paint fragments, forensic automotive paint examiners have turned to the paint data query (PDQ) database, which allows the forensic examiner to compare the layer sequence and color, texture, and composition of the sample to paint systems of the original equipment manufacturer (OEM). However, modern automotive paints have a thin color coat and this layer on a microscopic fragment is often too thin to obtain accurate chemical and topcoat color information. A search engine has been developed for the infrared (IR) spectral libraries of the PDQ database in an effort to improve discrimination capability and permit quantification of discrimination power for OEM automotive paint comparisons. The similarity of IR spectra of the corresponding layers of various records for original finishes in the PDQ database often results in poor discrimination using commercial library search algorithms. A pattern recognition approach employing pre-filters and a cross-correlation library search algorithm that performs both a forward and backward search has been used to significantly improve the discrimination of IR spectra in the PDQ database and thus improve the accuracy of the search. This improvement permits inter-comparison of OEM automotive paint layer systems using the IR spectra alone. Such information can serve to quantify the discrimination power of the original automotive paint encountered in casework and further efforts to succinctly communicate trace evidence to the courts.

scholarly journals A New Library-Search Algorithm for Mixture Analysis Using DART-MS

2021 ◽  
Author(s):  
Arun Moorthy ◽  
Edward Sisco
Keyword(s):  
Mass Spectrum ◽  
Mass Spectra ◽  
Search Algorithm ◽  
Collision Induced Dissociation ◽  
Two Stage ◽  
Library Search ◽  
Prototype Implementation ◽  
Search Results ◽  
Protonated Molecules ◽  
Acetyl Fentanyl

This manuscript introduces a new library-search algorithm for identifying components of a mixture using in-source collision-induced dissociation (is-CID) mass spectra. The two-stage search, titled the Inverted Library-Search Algorithm (ILSA), identifies potential components in a mixture by first searching its low fragmentation mass spectrum for target peaks, assuming these peaks are protonated molecules, and then scoring each target peak with possible library matches using one of two schemes. Utility of the ILSA is demonstrated through several example searches of model mixtures of acetyl fentanyl, benzyl fentanyl, amphetamine and methamphetamine searched against a small library of select compounds and the NIST DART-MS Forensics library. Discussion of the search results and several open areas of research to further extend the method are provided. A prototype implementation of the ILSA is available at <a href="https://github.com/asm3-nist/DART-MS-DST">https://github.com/asm3-nist/DART-MS-DST</a>.

scholarly journals Improvement of drug identification in urine by LC-QqTOF using a probability-based library search algorithm

2017 ◽  
Vol 3 ◽  
pp. 7-12 ◽  
Author(s):  
Jennifer M. Colby ◽  
Jeffery Rivera ◽  
Lyle Burton ◽  
Dave Cox ◽  
Kara L. Lynch
Keyword(s):  
Search Algorithm ◽  
Library Search ◽  
Drug Identification

scholarly journals A Fast and Memory‐Efficient Spectral Library Search Algorithm Using Locality‐Sensitive Hashing

PROTEOMICS ◽  
2020 ◽  
Vol 20 (21-22) ◽  
pp. 2000002 ◽  
Author(s):  
Lei Wang ◽  
Kaiyuan Liu ◽  
Sujun Li ◽  
Haixu Tang
Keyword(s):  
Search Algorithm ◽  
Locality Sensitive Hashing ◽  
Spectral Library ◽  
Library Search ◽  
Memory Efficient
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