We have contributed with a chapter about chemometric methods used in the framework of food authenticity (Authenticity and Chemometrics basics) in the book Chemometrics and Authenticity of Foods of Plant Origin, CRC Press, here the link
Out a new publication: “From the streets to the judicial evidence: determination of traditional illicit substances in drug seizures by a rapid and sensitive UHPLC-MS/MS-based platform”, have a look here.
We have developed a new analytical method for the identification of photodegradation products of Escitalopram, details are published here: Termopoli, V., Consonni, V., Ballabio, D., Todeschini, R., Orlandi, M., Gosetti, F. (2022) Identification of photodegradation products of Escitalopram in surface water by HPLC-MS/MS and preliminary characterization of their potential impact on the environment, Separations, 9, 289 [link]
Here our latest publication: “Multi-task neural networks and molecular fingerprints to enhance compound identification from LC-MS/MS data” Molecules (2022), 27, 5827 [link]. Data to reproduce the results are available at our website: https://michem.unimib.it/download/data/lc-ms-ms-to-fingerprints-dataset/
Our paper dealing with the application of multitask neural networks to predict molecular activity on nuclear receptors is now published, have a look here: https://doi.org/10.1002/cem.3325
We compared different appraoches for optimisation of multitask neural network hyperparameters on QSAR data, results were recently published in the following manuscript: Valsecchi, C., Consonni, V., Todeschini, R., Orlandi, M., Gosetti, F., Ballabio, D. (2021) Parsimonious Optimization of Multitask Neural Network Hyperparameters, Molecules, 26, 7254 Have a look here!
The manuscript about our latest partecipation in the CATMoS collaborative modelling project to predict Acute Oral Toxicity is not out, have a look: CATMoS: Collaborative Acute Toxicity Modeling Suite, Environmental Health Perspectives, 129, 47013 [link]
NURA (curated NUclear Receptor Activity dataset) is a curated dataset of nuclear receptor modulators. It contains bioactivity annotations for 15,206 molecules and 11 selected Nuclear Receptors (NRs) obtained by integrating and curating data from toxicological and pharmacological databases. The data can be dowloaded at Zenodo: https://doi.org/10.5281/zenodo.3991561; details on this dataset can be found here: Valsecchi, C., Grisoni, F., Motta, S., Bonati, L., Ballabio, D. (2020) NURA: a curated dataset of nuclear receptor modulators, Toxicology and Applied Pharmacology, 407, 115244 [link]
Todeschini, R., Consonni, V., Ballabio, D., Grisoni, F. (2020) Chemometrics for QSAR Modeling. In Comprehensive Chemometrics (Second Edition), S. Brown, R. Tauler, B. Walczak (Eds.), Elsevier [link]
Here a new chapter just published in the Encyclopedia of Analytical Chemistry (Wiley) on distance and simialrity measures for chemical data: Todeschini, R., Ballabio, D. and Consonni, V. (2020). Distances and Similarity Measures in Chemometrics and Chemoinformatics. In Encyclopedia of Analytical Chemistry, R.A. Meyers (Ed.) [link]