VirtuousMultiTaste: Predicting Multiple Taste Sensations with a Multi- objective ML-driven Method

Androutsos, L., Pallante, L. et al., ChemRxiv (2023). doi: https://doi.org/10.26434/chemrxiv-2023-k3rcq

Machine Learning Aided Molecular Modelling of Taste to Identify Food Fingerprints

Pallante, L., Cannariato, M. et al., Chemical Engineering Transactions (2023). doi: 10.3303/CET23102048

Toward a general and interpretable
umami taste predictor using
a multi‑objective machine learning
approach

Pallante, L., Korfiati, A., Androutsos, L. et al., Scientific Reports (2022). doi: 10.1038/s41598-022-25935-3

Informed classification of sweeteners/bitterants compounds via explainable machine learning

Maroni, G., Pallante, L., Di Benedetto, G., Deriu, M.A., Piga, D., Grasso, G. Current Research in Food Science. (2022). https://doi.org/10.1016/j.crfs.2022.11.014

A survey on computational taste predictors

Malavolta, M., Pallante, L., Mavkov, B., Stojceski, F., Grasso, G., Korfiati, A., Mavroudi, S., Kalogeras, A., Alexakos, C., Martos, V., Amoroso, D., Di Benedetto, G., Piga, D., Theofilatos, K., & Deriu, M. A. (2022).  European Food Research and Technology. https://doi.org/10.1007/s00217-022-04044-5

On the human taste perception: Molecular-level understanding empowered by computational methods

Pallante, L., Malavolta, M., Grasso, G., Korfiati, A., Mavroudi, S., Mavkov, B., Kalogeras, A., Alexakos, C., Martos, V., Amoroso, D., di Benedetto, G., Piga, D., Theofilatos, K., & Deriu, M. A. (2021). Trends in Food Science & Technology, 116, 445–459. https://doi.org/10.1016/j.tifs.2021.07.013

Extraction of physicochemical properties from the fluorescence spectrum with 1D convolutional neural networks: Application to olive oil

Visualizing Chlorophyll a Fluorescence: A Practical Demonstration

Artificial Intelligence (AI) as a complementary technology for agricultural Remote Sensing (RS) in plant physiology teaching

Learning about chlorophyll and anthocyanins as potential indicators of plant physiological state

Fungi, P-Solubilization, and Plant Nutrition

Analizando las posibles aplicaciones de los drones y los satélites en la enseñanza de Fisiología Vegetal

Martos Núñez, V. (2022).  ReiDoCrea: Revista Electrónica de Investigación Docencia Creativa, 90–93. https://doi.org/10.30827/Digibug.72480

Enseñanza del Análisis Sensorial en un Panel de Cata y su relación con las propiedades del Aceite de Oliva Virgen

Martos Núñez, V. (2022).  ReiDoCrea: Revista Electrónica de Investigación Docencia Creativa, 87–89. https://doi.org/10.30827/Digibug.72479

This is the Nut You Should be Eating for Better Gut Health

Giorgio Calabrese and Cinzia Myriam Calabrese, IntechOpen (2022). doi: 10.5772/intechopen.108567

Combating Salinity Through Natural Plant Extracts Based Biostimulants: A Review

Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques

Venturini, F., Sperti, M., Michelucci, U., Herzig, I., Baumgartner, M., Caballero, J. P., Jimenez, A., & Deriu, M. A. (2021). Foods, 10(5), 1010. https://doi.org/10.3390/foods10051010

JAK inhibitors in immune-mediated rheumatic diseases: From a molecular perspective to clinical studies

Sperti, M., Malavolta, M., Ciniero, G., Borrelli, S., Cavaglià, M., Muscat, S., Tuszynski, J. A., Afeltra, A., Margiotta, D. P. E., & Navarini, L. (2021). Journal of Molecular Graphics and Modelling, 104, 107789. https://doi.org/10.1016/j.jmgm.2020.107789

Use of machine learning to establish limits in the classification of hyperaccumulator plants growing on serpentine, gypsum and dolomite soils

Mota-Merlo, M., & Martos, V. (2021). Mediterranean Botany, 42, e67609. https://doi.org/10.5209/mbot.67609

A Model-Agnostic Algorithm for Bayes Error Determination in Binary Classification

Michelucci, U., Sperti, M., Piga, D., Venturini, F., & Deriu, M. A. (2021). Algorithms, 14(11), 301. https://doi.org/10.3390/a14110301

Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0

Martos, V., Ahmad, A., Cartujo, P., & Ordoñez, J. (2021). Applied Sciences, 11(13), 5911. https://doi.org/10.3390/app11135911

Fragmented blind docking: a novel protein-ligand binding prediction protocol

Grasso, G., Di Gregorio, A., Mavkov, B., Piga, D., Labate, G. F. D., Danani, A., & Deriu, M. A. (2021). Journal of Biomolecular Structure and Dynamics, 0(0), 1–10. https://doi.org/10.1080/07391102.2021.1988709

The Impact of Natural Compounds on S-Shaped Aβ42 Fibril: From Molecular Docking to Biophysical Characterization

Muscat, S., Pallante, L., Stojceski, F., Danani, A., Grasso, G., & Deriu, M. A. (2020). International Journal of Molecular Sciences, 21(6), 2017. https://doi.org/10.3390/ijms21062017

When Stiffness Matters: Mechanosensing in Heart Development and Disease

Gaetani, R., Zizzi, E. A., Deriu, M. A., Morbiducci, U., Pesce, M., & Messina, E. (2020). Frontiers in Cell and Developmental Biology, 8(May), 1–16. https://doi.org/10.3389/fcell.2020.00334

Remotely Piloted Aircraft (RPA) in Agriculture: A Pursuit of Sustainability

Ahmad, A., Ordoñez, J., Cartujo, P., & Martos, V. (2020). Agronomy, 11(1), 7. https://doi.org/10.3390/agronomy11010007