AI Medical Compendium Journal:
Journal of chromatography. A

Showing 31 to 40 of 66 articles

Accurate prediction of isothermal gas chromatographic Kováts retention indices.

Journal of chromatography. A
We describe a freely available web server called Retention Index Predictor (RIpred) (https://ripred.ca) that rapidly and accurately predicts Gas Chromatographic Kováts Retention Indices (RI) using SMILES strings as chemical structure input. RIpred pe...

Highly automatic and universal approach for pure ion chromatogram construction from liquid chromatography-mass spectrometry data using deep learning.

Journal of chromatography. A
Feature extraction is the most fundamental step when analyzing liquid chromatography-mass spectrometry (LC-MS) datasets. However, traditional methods require optimal parameter selections and re-optimization for different datasets, thus hindering effi...

An automated, low volume, and high-throughput analytical platform for aggregate quantitation from cell culture media.

Journal of chromatography. A
High throughput screening methods have driven a paradigm shift in biopharmaceutical development by reducing the costs of good manufactured (COGM) and accelerate the launch to market of novel drug products. Scale-down cell culture systems such as shak...

Deep learning-based method for automatic resolution of gas chromatography-mass spectrometry data from complex samples.

Journal of chromatography. A
Modern gas chromatography-mass spectrometry (GC-MS) is the workhorse for the high-throughput profiling of volatile compounds in complex samples. It can produce a considerable amount of two-dimensional data, and automatic methods are required to disti...

Artificial neural networks to model the enantioresolution of structurally unrelated neutral and basic compounds with cellulose tris(3,5-dimethylphenylcarbamate) chiral stationary phase and aqueous-acetonitrile mobile phases.

Journal of chromatography. A
Artificial neural networks (ANN; feed-forward mode) are used to quantitatively estimate the enantioresolution (Rs) in cellulose tris(3,5-dimethylphenylcarbamate) of chiral molecules from their structural information. To the best of our knowledge, for...

Can a computer "learn" nonlinear chromatography?: Physics-based deep neural networks for simulation and optimization of chromatographic processes.

Journal of chromatography. A
The design and optimization of chromatographic processes is essential for enabling efficient separations. To this end, hyperbolic partial differential equations (PDEs) along with nonlinear adsorption isotherms must be solved using computationally exp...

Convolutional neural network for automated peak detection in reversed-phase liquid chromatography.

Journal of chromatography. A
Although commercially available software provides options for automatic peak detection, visual inspection and manual corrections are often needed. Peak detection algorithms commonly employed require carefully written rules and thresholds to increase ...

Deep learning for retention time prediction in reversed-phase liquid chromatography.

Journal of chromatography. A
Retention time prediction in high-performance liquid chromatography (HPLC) is the subject of many studies since it can improve the identification of unknown molecules in untargeted profiling using HPLC coupled with high-resolution mass spectrometry. ...

Prediction of the chromatographic hydrophobicity index with immobilized artificial membrane chromatography using simple molecular descriptors and artificial neural networks.

Journal of chromatography. A
Screening of physicochemical properties should be considered one of the essential steps in the drug discovery pipeline. Among the available methods, biomimetic chromatography with an immobilized artificial membrane is a powerful tool for simulating i...