Milano Chemometrics and QSAR Research Group
Department of Earth and Environmental Sciences – University of Milano-Bicocca
Have a look to our latest publication: Grisoni, F., Consonni, V., Ballabio, D. (2019) Machine Learning Consensus to Predict the Binding to the Androgen Receptor within the CoMPARA project. Journal of chemical information and modeling, 59, 1839-1848 [link]
Data related to these models are available for download.
New chapter: Recent advances in High-Level Fusion Methods to classify multiple analytical chemical data (published in in Data Fusion Methodology and Applications, Elsevier).
Have a look!!!
we would like to announce that new versions of our toolboxes for MATLAB have been released. A graphical user interface (GUI), which allows an easy model calculation and analysis of results, is provided with all the toolboxes.
The Classification toolbox for MATLAB is a collection of MATLAB modules for calculating classification (supervised pattern recognition) multivariate models.
In this new release, Backpropagation Neural Networks (BPNN) was added as classification method and the maximum number of classes that can be loaded (and modelled) has been extended to 20.
The toolbox can be downloaded here.
The Kohonen and CPANN toolbox for MATLAB is a collection of MATLAB modules for training Kohonen Maps (Self Organising Maps, SOMs) and supervised SOMs.
In this new release, the maximum number of classes that can be loaded (and modelled) has been extended to 20. Numerical results related to the position of samples in the top map and net weights have been added to the results menu.
The toolbox can be downloaded here.
The PCA toolbox for MATLAB is a collection of MATLAB modules for calculating unsupervised multivariate models (PCA, MDS and Cluster Analysis).
In this new release, the maximum number of classes that can be loaded has been extended to 20.
The toolbox can be downloaded here.
Finally, have a look to our data repository where you can freely download available data.
E’ disponibile in formato pdf Introduzione alla Chemiometria di R. Todeschini, precedentemente pubblicato da Edises Napoli
Glad our publication is now availale: On the misleading use of Q2F3 for QSAR model comparison, Molecular Informatics (2019), 38, 1800029. Have a look!
la Società Italiana di Chemiometria – Associazione Culturale ha bandito il finanziamento di tre borse di studio volte ad incentivare la partecipazione di giovani meritevoli (non strutturati) al 10th Colloquium Chemiometricum Mediterraneum (due borse) e alla Conferentia Chemometrica (una borsa).
La data limite per l’invio delle domande è fissata, rispettivamente, al 28 Aprile e al 3 Agosto 2019.
Tutti i dettagli sui requisiti e le istruzioni per compilare ed inviare la richiesta di finanziamento sono disponibili sul sito del Gruppo di Chemiometria al link:
http://www.gruppochemiometria.it/index.php/news
Gruppo Italiano di Chemiometria on Facebook: https://www.facebook.com/gruppochemiometria/
Si segnala il seminario del Prof. Massimo Buscema (University of Colorado & SEMEION) “Real deep learning and artificial neural networks”, Lunedì 25 marzo 2019, Ore 15:00, Edificio U1 – Aula Marchetti, Università Milano – Bicocca (P.zza della Scienza, 1, 20126 Milano, Italy). A seguire, la Dr.ssa Francesca Grisoni (ETH Zurich, Dept. of Chemistry and Applied Biosciences) presenterà un case study dal titolo: “Recurrent Neural Networks for de novo drug design”. Maggiori informazioni e locandina del seminario.
Job opportunity at Roche as Research Informatics & Data Expert: https://www.linkedin.com/jobs/view/1071685102/
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Prof. Roberto Todeschini is guest editor of the special issue “QSAR and Chemoinformatics Tools for Modeling” for the International Journal of Molecular Science. More details here. |