Mass Spectral Similarity Mapping Applied to Fentanyl Analogs
| Autor: | William E. Wallace, Arun S. Moorthy, W.G. Mallard, Anthony J. Kearsley |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Type (model theory) 01 natural sciences Article Spectral line Pathology and Forensic Medicine Analytical Chemistry Fentanyl Set (abstract data type) 03 medical and health sciences 0302 clinical medicine Similarity (network science) Materials Chemistry medicine 030216 legal & forensic medicine Physical and Theoretical Chemistry Cluster analysis Spectroscopy business.industry 010401 analytical chemistry k-means clustering Pattern recognition Spectral similarity 0104 chemical sciences Artificial intelligence business Law medicine.drug |
| Zdroj: | Forensic Chem |
| DOI: | 10.26434/chemrxiv.11816841.v1 |
| Popis: | This manuscript outlines a straight-forward procedure for generating a map of similarity between spectra of a set. When applied to a reference set of spectra for Type I fentanyl analogs (molecules differing from fentanyl by a single modification), the map illuminates clustering that is applicable to automated structure assignment of unidentified molecules. An open-source software implementation that generates mass spectral similarity mappings of unknowns against a library of Type I fentanyl analog spectra is available at http://github.com/asm3-nist/FentanylClassifier. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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