VALSECCHI, CECILE

VALSECCHI, CECILE  

DIPARTIMENTO DI SCIENZE DELL'AMBIENTE E DELLA TERRA (DEPARTMENT OF EARTH AND ENVIRONMENTAL SCIENCES - DISAT)  

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Titolo Tipologia Data di pubblicazione Autori File
Multitask Learning for Quantitative Structure–Activity Relationships: A Tutorial 03 - Contributo in libro 2023 Valsecchi, CecileConsonni, VivianaBallabio, DavideTodeschini, Roberto +
Advancing the prediction of Nuclear Receptor modulators through machine learning methods 07 - Tesi di dottorato Bicocca post 2009 2022 VALSECCHI, CECILE
Expanding Antineoplastic Drugs Surface Monitoring Profiles: Enhancing of Zwitterionic Hydrophilic Interaction Methods 01 - Articolo su rivista 2022 Valsecchi, CecileConsonni, VivianaGosetti, FabioBallabio, Davide +
Evaluation of classification performances of minimum spanning trees by 13 different metrics 01 - Articolo su rivista 2022 Todeschini, RobertoValsecchi, Cecile
Predicting molecular activity on nuclear receptors by multitask neural networks 01 - Articolo su rivista 2022 Valsecchi C.Collarile M.Todeschini R.Ballabio D.Consonni V. +
Multi-Task Neural Networks and Molecular Fingerprints to Enhance Compound Identification from LC-MS/MS Data 01 - Articolo su rivista 2022 Consonni, VivianaGosetti, FabioTermopoli, VeronicaTodeschini, RobertoValsecchi, CecileBallabio, Davide
Predicting molecular activity on nuclear receptors with deep and machine learning 02 - Intervento a convegno 2021 Valsecchi,CGrisoni,FConsonni, VBallabio, DTodeschini, R
Nuclear receptor modulators: Catching information by machine learning 02 - Intervento a convegno 2021 Valsecchi, CecileConsonni, VivianaBallabio, DavideTodeschini, Roberto +
Classification of coralline algae using deep learning techniques on SEM images 02 - Intervento a convegno 2021 Piazza, GValsecchi, CSottocornola, GBasso, D
Enhanced LC-MS/MS spectra matching through multitask neural networks and molecular fingerprints 02 - Intervento a convegno 2021 Valsecchi, CBaccolo, GGosetti, FConsonni, VBallabio, DTodeschini, R +
Deep Ranking Analysis by Power Eigenvectors (DRAPE): A Study on the Human, Environmental and Economic Wellbeing of 154 Countries 03 - Contributo in libro 2021 Valsecchi, CTodeschini, R
Parsimonious optimization of multitask neural network hyperparameters 01 - Articolo su rivista 2021 Valsecchi, CecileConsonni, VivianaTodeschini, RobertoOrlandi, Marco EmilioGosetti, FabioBallabio, Davide
Deep Learning Applied to SEM Images for Supporting Marine Coralline Algae Classification 01 - Articolo su rivista 2021 Piazza, GiuliaValsecchi, CecileSottocornola, Gabriele
Consensus versus Individual QSARs in Classification: Comparison on a Large-Scale Case Study 01 - Articolo su rivista 2020 Valsecchi, CecileGrisoni, FrancescaConsonni, VivianaBallabio, Davide
NURA: A curated dataset of nuclear receptor modulators 01 - Articolo su rivista 2020 Valsecchi, CecileMotta, StefanoBonati, LauraBallabio, Davide +
Deep Ranking Analysis by Power Eigenvectors (DRAPE): A polypharmacology case study 01 - Articolo su rivista 2020 Valsecchi, CecileBallabio, DavideConsonni, VivianaTodeschini, Roberto
Similarity/Diversity Indices on Incidence Matrices Containing Missing Values 01 - Articolo su rivista 2020 Valsecchi, CTodeschini, R
Similarity/diversity indices on incidence matrices containing missing values 02 - Intervento a convegno 2019 Valsecchi, CTodeschini, R
Consensus Prediction of Androgen Receptor Activity within the CoMPARA Project 02 - Intervento a convegno 2019 Ballabio, DValsecchi, CGrisoni, FConsonni, VTodeschini, R +
QSAR modeling of Daphnia magna and fish toxicities of biocides using 2D descriptors 01 - Articolo su rivista 2019 Valsecchi C. +