Il prossimo Workshop del Gruppo di Chemiometria si terrà a L’Aquila dal 30 maggio al 1° giugno 2022. Il Workshop manterrà l’impostazione tradizionale: ciascun gruppo di ricerca/ente/azienda/singolo partecipante potrà richiedere uno slot temporale personalizzabile (tra 10 e 60 minuti) per la presentazione orale delle proprie attività chemiometriche in ambito di di ricerca, didattica e applicazioni.
Per maggiori informazioni: http://www.gruppochemiometria.it/index.php/workshop
News
Cecile Valsecchi PhD defense
Today Cecile Valsecchi successfully defended her PhD thesis: “Advancing the prediction of Nuclear Receptor modulators through machine learning methods”. She studied potential interactions between chemicals and nuclear receptors, with the dual purpose of developing in silico tools to search for new modulators and to identify possible endocrine disrupting chemicals.
Congrats! Really a great job!
If you are interested, the PhD thesis can be downloaded here: https://michem.unimib.it/download/phd-thesis/
Kohonen and CPANN Toolbox: new release 4.5 out!
A new release of the Kohonen and CPANN Toolbox (for Matlab) is now available! The toolbox is a collection of MATLAB modules for calculating Kohonen Maps and Counterpropagation Artificial Neural networs (CPANNs), Supervised Kohonen networks and XY-fused networks. In this new release, it is possible to have calculation on a GPU and RAM usage has been optimised to better deal with big data. The toolbox can be downloaded here.
Parsimonious optimization of multitask neural networks
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!
Welcome to Veronica Termopoli
Welcome to Veronica Termopoli, new member of the Milano Chemometrics and QSAR Research Group! Veronica has a strong background on chromatography and she will give her introductory seminar “New instrumental and applicative approaches in LC-MS” at our department next wednesday november 10th, more info here.
Classification toolbox: new release!
A new release of the classification toolbox for MATLAB is now available: variance scaling and range scaling have been added as approaches for column pre-processing. Basic row pre-processing methods have been added (standard normal variate, multiplicatve scatter correction, first and second derivative). Savitzky-Golay smoothing can now be applied to analytical spectral data. The layout of the calculation menu has been simplified. Download the latest version here!
Kohonen and CPANN Toolbox: new release out!
A new release of the Kohonen and CPANN Toolbox (for Matlab) is now available! The toolbox is a collection of MATLAB modules for calculating Kohonen Maps and Counterpropagation Artificial Neural networs (CPANNs), Supervised Kohonen networks and XY-fused networks. In this new release, it is possible to have calculation on a GPU. This can be helpfull when dealing with big data. The toolbox can be downloaded here.
Michem video to promote degrees in Chemical Sciences @ UNIMIB
We recently participated to the action promoted by the Degree in Chemical Sciences at the University of Milano – Bicocca to promote the courses around Italy. Here the result (in Italian…): https://www.youtube.com/watch?v=ClRF7sf0hxU
Kohonen and CPANN Toolbox: new release!
A new release of the Kohonen and CPANN Toolbox (for Matlab) is now available! The toolbox is a collection of MATLAB modules for calculating Kohonen Maps and Counterpropagation Artificial Neural networs (CPANNs), Supervised Kohonen networks and XY-fused networks. In this new release, the computational time for the calculation of SOMs has been significantly reduced. The toolbox can be downloaded here.
Regression toolbox for MATLAB now available!
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The Regression toolbox (for MATLAB) is a collection of MATLAB modules for calculating regression multivariate models: Ordinary Least Squares (OLS), Partial Least Squares (PLS), Principal Component Regression (PCR), Ridge regression, local regression based on K Nearest Neighbours (KNN) and Binned Nearest Neighbours (BNN) approaches, and variable selection approaches (All Subset Models, Forward selection, Genetic Algorithms and Reshaped Sequential Replacement).
The toolbox is freely available and can be downloaded here |