Milano Chemometrics and QSAR Research Group
Department of Earth and Environmental Sciences – University of Milano-Bicocca
Thursday 9 November 2023 at the Istituto Lombardo – Accademia di Scienze e Lettere in Milan prof. Todeschini was invited to hold a conference on the scientific activity of his great-grandfather prof. Wilhelm Körner entitled “Wilhelm Körner: dalla molecola alla struttura molecolare”. Slides are available at this link.
Which is the effect of different types of molecular fingerprints for exploring the chemical space of natural products? Have a look here: https://doi.org/10.26434/chemrxiv-2023-0m355
Random Forest has been added as classification method in the latest release of the Classification toolbox for MATLAB. The toolbox is available for download at this link: https://michem.unimib.it/download/matlab-toolboxes/classification-toolbox-for-matlab/
We have published a comprehensive review on classification-based chemoemtric approaches to predict taste of molecules, have a look!
Rojas, C., Ballabio, D., Consonni, V., Suárez-Estrella, D., Todeschini, R. (2023) Classification-based machine learning approaches to predict the taste of molecules: a review. Food Research International, 171, 113036 [link]
A new release of the Kohonen and CPANN toolbox (4.6) is now available. In this release, GPU and CPU calculation has been improved. The Kohonen and CPANN toolbox for MATLAB is a collection of MATLAB modules for training Kohonen Maps (Self Organising Maps, SOMs), Counterpropagation Artificial Neural networs (CPANNs), Supervised Kohonen networks (SKN), XY-fused networks (XY-F). It can be downloaded here: https://michem.unimib.it/download/matlab-toolboxes/kohonen-and-cpann-toolbox-for-matlab/
Here our latest poublication, which was the first product of the PhD project of Emmanuel Cruz in collaboration with the Laboratory for Provenance Studies (University of Milano-Bicocca), the Department of Analytical Chemistry (University of the Basque Country) and IKERBASQUE (Basque Society for the Promotion of Science):
Cruz Muñoz, E., Gosetti, F., Ballabio, D., Andò, S., Gómez-Laserna, O., Amigo, J.M., Garzanti, E. (2023) Characterization of pyrite weathering products by Raman hyperspectral imaging and chemometrics techniques. Microchemical Journal, 190, 108655 [link]
Visit and follow our twitter profile!! https://twitter.com/MiChemQSAR
Membrane introduction mass spectrometry (MIMS) is a direct mass spectrometry technique used to monitor online chemical systems or quickly quantify trace levels of different groups of compounds in complex matrices without extensive sample preparation steps and chromatographic separation. Here a recent review:
V. Termopoli, M. Piergiovanni, D. Ballabio, V. Consonni, E. Cruz Muñoz, F. Gosetti (2023) Condensed phase membrane introduction mass spectrometry: a direct alternative to fully exploit the mass spectrometry potential in environmental sample analysis, Separations, 10, 139, https://doi.org/10.3390/separations10020139
We have published a new chapter, which is a tutorial for training multitask neural networks in the framework of QSAR modelling, have a look here: https://doi.org/10.1007/978-3-031-20730-3_8
Valsecchi, C., Grisoni, F., Consonni, V., Ballabio, D., Todeschini, R. (2023). Multitask Learning for Quantitative Structure–Activity Relationships: A Tutorial. In Machine Learning and Deep Learning in Computational Toxicology. Computational Methods in Engineering & the Sciences. (Hong, H., eds), Springer
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