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
QSAR models to predict Acute Oral Systemic Toxicity 02 - Intervento a convegno 2018 VALSECCHI, CECILEViviana ConsonniRoberto TodeschiniDavide Ballabio +
Structural alerts for the identification of bioaccumulative compounds 02 - Intervento a convegno 2018 Cecile ValsecchiFrancesca GrisoniViviana ConsonniDavide Ballabio
Activity cliffs and structural cliffs for categorical responses 01 - Articolo su rivista 2018 Todeschini, RValsecchi, C
Consensus Prediction of Androgen Receptor Activity within the CoMPARA Project 02 - Intervento a convegno 2019 Ballabio, DValsecchi, CGrisoni, FConsonni, VTodeschini, R +
Similarity/diversity indices on incidence matrices containing missing values 02 - Intervento a convegno 2019 Valsecchi, CTodeschini, R
QSAR modeling of Daphnia magna and fish toxicities of biocides using 2D descriptors 01 - Articolo su rivista 2019 Valsecchi C. +
Structural alerts for the identification of bioaccumulative compounds 01 - Articolo su rivista 2019 Valsecchi, CGrisoni, FConsonni, VBallabio, D
Similarity/Diversity Indices on Incidence Matrices Containing Missing Values 01 - Articolo su rivista 2020 Valsecchi, CTodeschini, R
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
Consensus versus Individual QSARs in Classification: Comparison on a Large-Scale Case Study 01 - Articolo su rivista 2020 Valsecchi, CecileGrisoni, FrancescaConsonni, VivianaBallabio, Davide
Nuclear receptor modulators: Catching information by machine learning 02 - Intervento a convegno 2021 Valsecchi, CecileConsonni, VivianaBallabio, DavideTodeschini, Roberto +
Predicting molecular activity on nuclear receptors with deep and machine learning 02 - Intervento a convegno 2021 Valsecchi,CGrisoni,FConsonni, VBallabio, DTodeschini, R
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 +
Classification of coralline algae using deep learning techniques on SEM images 02 - Intervento a convegno 2021 Piazza, GValsecchi, CSottocornola, GBasso, D
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
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
Advancing the prediction of Nuclear Receptor modulators through machine learning methods 07 - Tesi di dottorato Bicocca post 2009 2022 VALSECCHI, CECILE
Evaluation of classification performances of minimum spanning trees by 13 different metrics 01 - Articolo su rivista 2022 Todeschini, RobertoValsecchi, Cecile