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Journal of Chromatography. A|August 7, 2024
Large-scale statistical study of the dependence of retention index on heating rate in temperature-programmed gas chromatographyDmitriy D Matyushin, Anastasia Yu SholokhovaJournal of Mass Spectrometry : JMS|August 4, 2026
Interactive Software for Interpreting and Curating High-Resolution Electron Ionization Mass SpectraDmitriy D Matyushin, Anastasia Yu SholokhovaJournal of Separation Science|November 4, 2024
Ready-to-use Models Built Using a Diverse Set of 266 Aroma Compounds for the Estimation of Gas Chromatographic Retention Indices for the 50%-Cyanopropylphenyl-50%-Dimethylpolysiloxane Stationary PhaseAnastasia Yu Sholokhova, Dmitriy D MatyushinInternational Journal of Molecular Sciences|September 10, 2021
Deep Learning Based Prediction of Gas Chromatographic Retention Indices for a Wide Variety of Polar and Mid-Polar Liquid Stationary PhasesDmitriy D Matyushin, Anastasia Yu Sholokhova, Aleksey K BuryakAnalytical Chemistry|September 2, 2020
Deep Learning Driven GC-MS Library Search and Its Application for MetabolomicsDmitriy D Matyushin, Anastasia Yu Sholokhova, Aleksey K BuryakJournal of Chromatography. A|August 14, 2019
A deep convolutional neural network for the estimation of gas chromatographic retention indicesDmitriy D Matyushin, Anastasia Yu Sholokhova, Aleksey K BuryakInternational Journal of Molecular Sciences|December 17, 2024
Uncertainty Quantification and Flagging of Unreliable Predictions in Predicting Mass Spectrometry-Related Properties of Small Molecules Using Machine LearningDmitriy D Matyushin, Ivan A Burov, Anastasia Yu SholokhovaAnalytical and Bioanalytical Chemistry|September 27, 2024
Critical evaluation of the NIST retention index database reliability with specific examplesDmitriy D Matyushin, Anastasia E Karnaeva, Anastasia Yu SholokhovaJournal of Chromatography. A|July 12, 2024
Quantitative structure-retention relationships for pyridinium-based ionic liquids used as gas chromatographic stationary phases: convenient software and assessment of reliability of the resultsAnastasia Yu Sholokhova, Dmitriy D Matyushin, Mikhail V ShashkovChemosphere|July 21, 2022
Machine learning-assisted non-target analysis of a highly complex mixture of possible toxic unsymmetrical dimethylhydrazine transformation products with chromatography-mass spectrometryAnastasia Yu Sholokhova, Oksana I Grinevich, Dmitriy D Matyushin, et al.Pageof 3