3 citations · 5 across the 6 of their papers we have counts for
6 papers
Explainable Machine Learning and Deep Learning Models for Predicting TAS2R-Bitter Molecule Interactions
Francesco Ferri, Marco Cannariato, Lorenzo Pallante +2
This work aims to develop explainable models to predict the interactions between bitter molecules and TAS2Rs via traditional machine-learning and deep-learning methods starting fro…
LightCPPgen: An Explainable Machine Learning Pipeline for Rational Design of Cell Penetrating Peptides
Gabriele Maroni, Filip Stojceski, Lorenzo Pallante +3
Cell-penetrating peptides (CPPs) are powerful vectors for the intracellular delivery of a diverse array of therapeutic molecules. Despite their potential, the rational design of CP…
Dataset of Fluorescence Spectra and Chemical Parameters of Olive Oils
Francesca Venturini, Michela Sperti, Umberto Michelucci +3
This dataset encompasses fluorescence spectra and chemical parameters of 24 olive oil samples from the 2019-2020 harvest provided by the producer Conde de Benalua, Granada, Spain.…
Physico-chemical properties extraction from the fluorescence spectrum with 1D-convolutional neural networks: application to olive oil
Francesca Venturini, Michela Sperti, Umberto Michelucci +3
The olive oil sector produces a substantial impact in the Mediterranean's economy and lifestyle. Many studies exist which try to optimize the different steps in the olive oil's pro…
A Model-Agnostic Algorithm for Bayes Error Determination in Binary Classification
Umberto Michelucci, Michela Sperti, Dario Piga +2
This paper presents the intrinsic limit determination algorithm (ILD Algorithm), a novel technique to determine the best possible performance, measured in terms of the AUC (area un…
Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques
Francesca Venturini, Michela Sperti, Umberto Michelucci +5
Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud…