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]
News
New book chapter: Chemometrics for QSAR Modeling
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]
New chapter on distance and similarity measures
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]
Bayes and majority voting consensus for MATLAB
New Matlab toolbox available for the calculation of high level data fusion (consensus) approaches (majority voting and Bayes consensus with discrete probability distributions): https://michem.unimib.it/download/data/bayes-and-majority-voting-consensus-for-matlab/
Consensus to enanche QSAR modelling: a large-scale case study
Our latest publication on data fusion, consensus and QSAR is available on line: Valsecchi, C., Grisoni, F., Consonni, V., Ballabio, D. (2020), Consensus versus individual QSARs in classification: comparison on a large-scale case study, Journal of chemical information and modeling, 60, 1215-1223 [link]
CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity
This publication was the outcome of a great collaborative project for the identification of Androgen Receptor Activity through machine learning and consensus analysis, check it out: Mansouri, K. et al. (2020) CoMPARA : Collaborative Modeling Project for Androgen Receptor Activity. Environmental Health Perspectives, 128, 027002 [link]
Geographical identification of Chianti red wines
This scientific publication was the outcome of a long collaboration with Ruffino, check it out: Bronzi, B., Brilli, C., Beone, G.M., Fontanella, M.C., Ballabio, D., Todeschini, R., Consonni, V., Grisoni, F., Parri, F., Buscema, M. (2020), Geographical identification of Chianti red wine based on ICP-MS element composition, Food Chemistry, 315, 126248 [link]
Available PhD position for Molecular Modeling and Virtual Screening
Available PhD position for Molecular Modeling and Virtual Screening for Rational Design of Tubulin-Protein Interaction Modulators at TubInTrain (European Joint Doctorate on chemistry and biology). For further info: https://www.tubintrain.eu/phd-project-esr2/
Prof. Todeschini valedictory lecture
The valedictory lecture of Prof. Todeschini will take place on monday 16th of december 2019, 10:30, room U3-01 (building U3 – Università degli Studi di Milano – Bicocca): “Una vita per la ricerca, la ricerca di una vita” [link]
Classification toolbox for MATLAB: new release
In this new release (5.4), class modelling methods (SIMCA, Potential Functions – Kernel Density Estimators, UNEQ) can now be calculated on a specific target class. The toolbox can be downloaded here.