Abstract The Human Metabolome Database or HMDB (https://hmdb. ca) has been providing
comprehensive reference information about human metabolites and their associated …

Chemometrics and machine learning are artificial intelligence-based methods stirring a
transformative change in chemistry. Organic synthesis, drug discovery and analytical …

Methods for assessing compound identification confidence in metabolomics and related
studies have been debated and actively researched for the past two decades. The earliest …

The goal of the present study was to use a quantitative structure-retention relationship
(QSRR) for the retention indices of 1179 flavour and fragrance organic compounds using the …

Prediction of gas chromatographic retention indices based on compound structure is an
important task for analytical chemistry. The predicted retention indices can be used as a …

We describe a freely available web server called Retention Index Predictor
(RIpred)(https://ripred. ca) that rapidly and accurately predicts Gas Chromatographic Kováts …

The limited information in existing mass spectral libraries hinders an accurate understanding
of the composition, behavior, and toxicity of organic pollutants. In this study, a total of 350 …

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 …

The quality of the coffee beverage is related to the chemical, physical, and sensory attributes
of the coffee beans that vary with the geographic location of the crop, genetic factors, and …

This study aims to evaluate the implementation and effectiveness of the Adaptive Neuro-
Fuzzy Inference System (ANFIS) based Quantitative Structure Retention Relationship …