FederEI: Federated Library Matching Framework for Electron Ionization Mass Spectrum Based Compound Identification.

Mass spectrometry (MS) is a powerful tool for compound structure elucidation, crucial in various domains including pharmaceuticals, chemical synthesis, environmental analysis, and metabolomics. Compound identification via spectral matching relies heavily on reference libraries, yet existing universal libraries may lack comprehensiveness. Laboratories often create their own libraries, leading to fragmentation within the scientific community.

A Comprehensive Comparative Analysis of Deep Learning Based Feature Representations for Molecular Taste Prediction.

Taste determination in small molecules is critical in food chemistry but traditional experimental methods can be time-consuming. Consequently, computational techniques have emerged as valuable tools for this task. In this study, we explore taste prediction using various molecular feature representations and assess the performance of different machine learning algorithms on a dataset comprising 2601 molecules.