14 papers · ranked by Valyu relevance
Authors not listed
Tandem mass spectrometry (MS/MS) fragmentation is conventionally understood as stochastic bond cleavage determined by thermochemical bond strengths and collision energies. We demonstrate that fragmentation is a deterministic categorical state progression governed by phase-lock network topology, where fragment…
Eleni Litsa, Vijil Chenthamarakshan, Payel Das, Lydia Kavraki
Elucidating the structure of a chemical compound is a fundamental task in chemistry with application in multiple domains including the emerging field of metabolomics, with promising applications in drug discovery, precision medicine, and biomarker discovery. The common practice for elucidating the structure of a…
Wout Bittremieux, Mingxun Wang, Pieter C. Dorrestein
Background: Spectral library searching is currently the most common approach for compound annotation in untargeted metabolomics. Spectral libraries applicable to liquid chromatography mass spectrometry have grown in size over the past decade to include hundreds of thousands to millions of mass spectra and tens of…
Joshua Klein, Henry Lam, Tytus Mak, Wout Bittremieux + 22 more
Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization…
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Environmental damping in molecular spectroscopy is commonly treated as a phenomenological source of decoherence and spectral broadening, leading to a monotonic reduction of spectral intensity. Here we show that this assumption is not generally valid. Using a vibronically resolved response-function framework, we…
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This paper formally defines an operational isomorphism between spectral damping in molecular vibronic systems and neuromodulatory control in biological sensory systems. Without asserting causal continuity or physical identity across scales, we show that both domains instantiate the same class of output-selective…
Denis Tikhonov
Here, we present a new approach for obtaining radial distribution functions (RDF) from the electron diffraction data using a regularized weighted sine least-squares spectral analysis (rwsLSSA). It allows for explicitly transferring the measured experimental uncertainties in the reduced molecular scattering function to…
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Nuclear magnetic resonance spectroscopy (NMR) plays a key role for the analysis of a plethora of molecules, including natural products and drug-like organic molecules. For such cases 1H NMR spectra have proven imperative because of their high sensitivity. However, these spectra are complicated by complex multiplet…
Corinna Brungs, Robin Schmid, Steffen Heuckeroth, Aninda Mazumdar + 8 more
Untargeted analysis based on high-resolution mass spectrometry is a key tool in clinical metabolomics, natural product discovery, and exposomics, with compound identification remaining the major bottleneck. Currently, MS2 fragmentation data and spectral library matching are the standard workflow for confident compound…
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Vaccination is a highly efficient strategy in controlling infections. Aluminum-containing adjuvants have long been used to enhance immunogenicity, but quantification of adsorbed antigens remains analytically challenging. This study uses Raman spectroscopy, a powerful, non-destructive technique, augmented by machine…
Keisuke Ozawa
Statistically weighted principal component analysis (wPCA) is widely used to reduce the noise of scanning transmission electron microscopy-energy-dispersive X-ray (STEM-EDX) spectroscopy data. It is beneficial to retain the spatial resolution of observation in each step of the analysis, but the direct application of…
Chris Waudby, John Christodoulou
Non-uniform weighted sampling (NUWS) is a simple method for multi-dimensional NMR spectroscopy in which window functions are applied during acquisition by sampling varying numbers of scans across indirect dimensions. While NUWS was previously shown to provide modest increases in sensitivity, here we describe a…
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Structural determination of molecules using solution-state nuclear magnetic resonance (NMR) is a time-consuming effort mostly due to spectral analysis and correlation of spectral features with structural motifs. A few machine learning methods exist to aid this step of the workflow, requiring at least 1H and 13C…
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Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) spectral images, without relying on prior chemical knowledge. The potential of machine learning for chemical…