AIMC Topic: Chromatography, Liquid

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Current trends in chromatographic prediction using artificial intelligence and machine learning.

Analytical methods : advancing methods and applications
Artificial intelligence (AI) and machine learning (ML) gained tremendous growth and are rapidly becoming popular in various fields of prediction due to their potential abilities, accuracy, and speed. Machine learning algorithms employ historical data...

Using Machine Learning To Predict Partition Coefficient (Log ) and Distribution Coefficient (Log ) with Molecular Descriptors and Liquid Chromatography Retention Time.

Journal of chemical information and modeling
During preclinical evaluations of drug candidates, several physicochemical (p-chem) properties are measured and employed as metrics to estimate drug efficacy in vivo. Two such p-chem properties are the octanol-water partition coefficient, Log , and d...

An Interpretable Deep Learning Approach for Biomarker Detection in LC-MS Proteomics Data.

IEEE/ACM transactions on computational biology and bioinformatics
Analyzing mass spectrometry-based proteomics data with deep learning (DL) approaches poses several challenges due to the high dimensionality, low sample size, and high level of noise. Additionally, DL-based workflows are often hindered to be integrat...

Fusion of Quality Evaluation Metrics and Convolutional Neural Network Representations for ROI Filtering in LC-MS.

Analytical chemistry
Region of interest (ROI) extraction is a fundamental step in analyzing metabolomic datasets acquired by liquid chromatography-mass spectrometry (LC-MS). However, noises and backgrounds in LC-MS data often affect the quality of extracted ROIs. Therefo...

Multi-Pesticide Residue Analysis Method Designed for the Robot Experimenters.

Journal of agricultural and food chemistry
Robots replacing humans as the executioners is crucial work for intelligent multi-pesticide residue analysis to maximize reproducibility and throughput while minimizing the expertise required to perform the entire process. Traditional analysis method...

Development of Liquid Chromatographic Retention Index Based on Cocamide Diethanolamine Homologous Series (C()-DEA).

Analytical chemistry
There is a growing need for indexing and harmonizing retention time (tR) data in liquid chromatography derived under different conditions to aid in the identification of compounds in high resolution mass spectrometry (HRMS) based suspect and nontarge...

An automated online three-phase electro-extraction setup with machine-vision process monitoring hyphenated to LC-MS analysis.

Analytica chimica acta
Sample preparation is a labor-intensive and time-consuming procedure, especially for the bioanalysis of small-volume samples with low-abundant analytes. To minimize losses and dilution, sample preparation should ideally be hyphenated to downstream on...

Multi-Task Neural Networks and Molecular Fingerprints to Enhance Compound Identification from LC-MS/MS Data.

Molecules (Basel, Switzerland)
Mass spectrometry (MS) is widely used for the identification of chemical compounds by matching the experimentally acquired mass spectrum against a database of reference spectra. However, this approach suffers from a limited coverage of the existing d...

Image classification combined with faster R-CNN for the peak detection of complex components and their metabolites in untargeted LC-HRMS data.

Analytica chimica acta
Peak detection of untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) data is a key step to identify the metabolic status of the drugable chemicals and extracts from functional foods or herbs. Nevertheless, the existing appro...

Identification of Nonvolatile Migrates from Food Contact Materials Using Ion Mobility-High-Resolution Mass Spectrometry and in Silico Prediction Tools.

Journal of agricultural and food chemistry
The identification of migrates from food contact materials (FCMs) is challenging due to the complex matrices and limited availability of commercial standards. The use of machine-learning-based prediction tools can help in the identification of such c...