Molecular fingerprints for exploring the chemical space of natural products

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We evaluated the effectiveness of multiple types of fingerprints for representing the chemical space of natural substances. The code and data to reproduce the results are also available in the study: Boldini, D., Ballabio, D., Consonni, V., Todeschini, R., Grisoni, F., Sieber, S.A. (2024) Effectiveness of molecular fingerprints for exploring the chemical space of natural products, Journal of Cheminformatics 16, 35 (2024), https://doi.org/10.1186/s13321-024-00830-3

A new metric to assess the degree of accuracy of consensus predictions

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We proposed a new heuristic metric to assess the degree of accuracy of consensus predictions. It can assist the mapping of reliability in prediction and enhance the delineation of a safe zone, where consensus predictions are expected to have better accuracy. All details are available in the following publication, have a look! We also provide data and code to calculate it, here!

V. Consonni, R. Todeschini, M. Orlandi, D. Ballabio (2024) Kernel-based mapping of reliability in predictions for consensus modelling, Chemometrics and Intelligent Laboratory Systems 246, 105085, https://doi.org/10.1016/j.chemolab.2024.105085

QSAR for REACH

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Milano Chemometrics has been involved in several projects related to the use of QSAR for the REACH registration of chemicals. If you are interested in collaboration on these topics, read here.

Molecular Descriptors Data Base

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The MOLE db – Molecular Descriptors Data Base is a free on-line database constituted of 1124 molecular descriptors calculated on 234773 molecules, released by Milano Chemometrics and QSAR Research Group: explore the MOLE db data base here!