AIMC Topic: Mass Spectrometry

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Prosit Transformer: A transformer for Prediction of MS2 Spectrum Intensities.

Journal of proteome research Apr 12, 2022
Machine learning has been an integral part of interpreting data from mass spectrometry (MS)-based proteomics for a long time. Relatively recently, a machine-learning structure appeared successful in other areas of bioinformatics, Transformers. Furthe...
Machine Learning Proteomics Mass Spectrometry Neural Networks, Computer Amino Acid Sequence
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automRm: An R Package for Fully Automatic LC-QQQ-MS Data Preprocessing Powered by Machine Learning.

Analytical chemistry Apr 12, 2022
Preprocessing of liquid chromatography-mass spectrometry (LC-MS) raw data facilitates downstream statistical and biological data analyses. In the case of targeted LC-MS data, consistent recognition of chromatographic peaks is a main challenge, in par...
Mass Spectrometry Chromatography, Liquid Hydrophobic and Hydrophilic Interactions Machine Learning Software
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Fully automatic resolution of untargeted GC-MS data with deep learning assistance.

Talanta Mar 26, 2022
DeepResolution (Deep learning-assisted multivariate curve Resolution) has been proposed to solve the co-eluting problem for GC-MS data. However, DeepResolution models must be retrained when encountering unknown components, which is undoubtedly time-c...
Deep Learning Mass Spectrometry Fatty Acids Gas Chromatography-Mass Spectrometry Humans Neural Networks, Computer Male
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Utilization of Machine Learning for the Differentiation of Positional NPS Isomers with Direct Analysis in Real Time Mass Spectrometry.

Analytical chemistry Mar 17, 2022
The differentiation of positional isomers is a well established analytical challenge for forensic laboratories. As more novel psychoactive substances (NPSs) are introduced to the illicit drug market, robust yet efficient methods of isomer identificat...
Isomerism Machine Learning Mass Spectrometry
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A non-invasive method for concurrent detection of early-stage women-specific cancers.

Scientific reports Feb 10, 2022
We integrated untargeted serum metabolomics using high-resolution mass spectrometry with data analysis using machine learning algorithms to accurately detect early stages of the women specific cancers of breast, endometrium, cervix, and ovary across ...
Women's Health Early Detection of Cancer Metabolomics Genital Neoplasms, Female Middle Aged Mass Spectrometry Aged, 80 and over Young Adult Adult Sensitivity and Specificity Breast Neoplasms Biomarkers, Tumor Data Analysis Female Aged Humans Machine Learning
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Inferring protein expression changes from mRNA in Alzheimer's dementia using deep neural networks.

Nature communications Feb 3, 2022
Identifying the molecular systems and proteins that modify the progression of Alzheimer's disease and related dementias (ADRD) is central to drug target selection. However, discordance between mRNA and protein abundance, and the scarcity of proteomic...
Transcriptome Deep Learning Cognitive Dysfunction Aged, 80 and over Male Proteomics Proteome Mass Spectrometry Dementia RNA-Seq RNA, Messenger Humans Neural Networks, Computer Brain Female Aged Alzheimer Disease Protein Biosynthesis
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Quantitative structure retention relationship (QSRR) modelling for Analytes' retention prediction in LC-HRMS by applying different Machine Learning algorithms and evaluating their performance.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences Jan 19, 2022
In metabolomics, retention prediction methods have been developed based on the structural and physicochemical characteristics of analytes. Such methods employ regression models, harnessing machine learning algorithms mapping experimentally derived re...
Metabolomics Chromatography, Liquid Molecular Structure Bayes Theorem Linear Models Databases, Chemical Algorithms Organic Chemicals Mass Spectrometry Machine Learning
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A novel method for micropollutant quantification using deep learning and multi-objective optimization.

Water research Jan 15, 2022
Micropollutants (MPs) released into aquatic ecosystems have adverse effects on public health. Hence, monitoring and managing MPs in aquatic systems are imperative. MPs can be quantified by high-resolution mass spectrometry (HRMS) with stable isotope-...
Reference Standards Deep Learning Mass Spectrometry Isotopes Ecosystem
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Pyrrovobasine, hybrid alkylated pyrraline monoterpene indole alkaloid pseudodimer discovered using a combination of mass spectral and NMR-based machine learning annotations.

Organic & biomolecular chemistry Dec 22, 2021
A new vobasine-tryptamine-based monoterpene indole alkaloid pseudodimer was isolated from the stem bark of . As a minor constituent occurring in a thoroughly investigated plant, this molecule was targeted based on a molecular networking strategy and ...
Pyrroles Norleucine Indole Alkaloids Monoterpenes Machine Learning Magnetic Resonance Spectroscopy Mass Spectrometry Voacanga Alkylation
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Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor.

Thoracic cancer Nov 23, 2021
BACKGROUND: Rapid intraoperative diagnosis for unconfirmed pulmonary tumor is extremely important for determining the optimal surgical procedure (lobectomy or sublobar resection). Attempts to diagnose malignant tumors using mass spectrometry (MS) hav...
Male Female Adenocarcinoma of Lung Humans Lung Neoplasms Aged Artificial Intelligence Mass Spectrometry Colorectal Neoplasms
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