Viviana Consonni

发表

Assessing the validity of QSARs for ready biodegradability of chemicals: an applicability domain perspective.

Roberto Todeschini, Faizan Sahigara, Davide Ballabio, 2014, Current computer-aided drug design.

Evaluation of model predictive ability by external validation techniques

Davide Ballabio, Roberto Todeschini, Viviana Consonni, 2010 .

Paolo Massimo Buscema, Roberto Todeschini, Peter Willett, 2012, J. Chem. Inf. Model..

Molecular Descriptors for Structure-Activity Applications: A Hands-On Approach.

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2018, Methods in molecular biology.

Impact of Molecular Descriptors on Computational Models.

Roberto Todeschini, Viviana Consonni, Francesca Grisoni, 2018, Methods in molecular biology.

Structural alerts for the identification of bioaccumulative compounds

Davide Ballabio, Viviana Consonni, Francesca Grisoni, 2018, Integrated environmental assessment and management.

Mixtures, metabolites, ionic liquids: a new measure to evaluate similarity between complex chemical systems

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2016, Journal of Cheminformatics.

Structure/Response Correlations and Similarity/Diversity Analysis by GETAWAY Descriptors, 2. Application of the Novel 3D Molecular Descriptors to QSAR/QSPR Studies

Paola Gramatica, Roberto Todeschini, Viviana Consonni, 2002, J. Chem. Inf. Comput. Sci..

Machine Learning Consensus To Predict the Binding to the Androgen Receptor within the CoMPARA Project

Davide Ballabio, Viviana Consonni, Francesca Grisoni, 2019, J. Chem. Inf. Model..

Mapping of Activity through Dichotomic Scores (MADS): A new chemoinformatic approach to detect activity‐rich structural regions

Davide Ballabio, Roberto Todeschini, Viviana Consonni, 2018 .

Handbook of Molecular Descriptors

Roberto Todeschini, Viviana Consonni, R. Todeschini, 2002 .

Appendix C. Software

Roberto Todeschini, Viviana Consonni, 2008 .

Consensus versus Individual QSARs in Classification: Comparison on a Large-Scale Case Study

Davide Ballabio, Viviana Consonni, Francesca Grisoni, 2020, J. Chem. Inf. Model..

Molecular descriptors for chemoinformatics

Roberto Todeschini, Viviana Consonni, R. Todeschini, 2009 .

N3 and BNN: Two New Similarity Based Classification Methods in Comparison with Other Classifiers

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2015, J. Chem. Inf. Model..

Qualitative consensus of QSAR ready biodegradability predictions

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2016 .

Investigating the mechanisms of bioconcentration through QSAR classification trees.

Roberto Todeschini, Marco Vighi, Viviana Consonni, 2016, Environment international.

Comments on the Definition of the Q2 Parameter for QSAR Validation

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2009, J. Chem. Inf. Model..

Quantitative Structure − Activity Relationship Models for Ready Biodegradability of Chemicals

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2013 .

Comparison of Different Approaches to Define the Applicability Domain of QSAR Models

Roberto Todeschini, Faizan Sahigara, Davide Ballabio, 2012, Molecules.

On the Misleading Use of QF32 for QSAR Model Comparison

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2018, Molecular informatics.

Defining a novel k-nearest neighbours approach to assess the applicability domain of a QSAR model for reliable predictions

Roberto Todeschini, Faizan Sahigara, Davide Ballabio, 2013, Journal of Cheminformatics.

Introduction to MOLE DB - on-line Molecular Descriptors Database

Davide Ballabio, Roberto Todeschini, Viviana Consonni, 2009 .

Integrated QSAR Models to Predict Acute Oral Systemic Toxicity

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2018, Molecular informatics.

Predicting molecular activity on nuclear receptors by multitask neural networks

Davide Ballabio, Viviana Consonni, Francesca Grisoni, 2020, Journal of Chemometrics.

Structure-Activity Relationships by autocorrelation descriptors and genetic algorithms

Roberto Todeschini, Viviana Consonni, R. Todeschini, 2011 .

Characterization of DNA Primary Sequences by a New Similarity/Diversity Measure Based on the Partial Ordering

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2006, J. Chem. Inf. Model..

Structure/Response Correlations and Similarity/Diversity Analysis by GETAWAY Descriptors, 1. Theory of the Novel 3D Molecular Descriptors

Roberto Todeschini, Viviana Consonni, Manuela Pavan, 2002, J. Chem. Inf. Comput. Sci..

Scaffold hopping from natural products to synthetic mimetics by holistic molecular similarity

Gisbert Schneider, Viviana Consonni, Francesca Grisoni, 2018, Communications Chemistry.

A MATLAB toolbox for multivariate regression coupled with variable selection

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2021 .

Nuclear receptor modulators: Catching information by machine learning

Davide Ballabio, Viviana Consonni, Francesca Grisoni, 2021, Biomedical Science and Engineering.

QSAR models for bioconcentration: is the increase in the complexity justified by more accurate predictions?

Roberto Todeschini, Marco Vighi, Viviana Consonni, 2015, Chemosphere.

CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

Ruili Huang, Scott Boyer, Xin Hu, 2020, Environmental health perspectives.

Prediction of Acute Aquatic Toxicity toward Daphnia Magna by using the GA-kNN Method

Roberto Todeschini, Igor V Tetko, Davide Ballabio, 2014, Alternatives to laboratory animals : ATLA.

Detecting the bioaccumulation patterns of chemicals through data-driven approaches.

Marco Vighi, Viviana Consonni, Francesca Grisoni, 2018, Chemosphere.

Acceptable‐by‐design QSARs to predict the dietary biomagnification of organic chemicals in fish

Marco Vighi, Viviana Consonni, Francesca Grisoni, 2018, Integrated environmental assessment and management.

Descriptors from Molecular Geometry

Roberto Todeschini, Viviana Consonni, R. Todeschini, 2008 .

The K correlation index: theory development and its application in chemometrics

Roberto Todeschini, Viviana Consonni, A. Maiocchi, 1999 .

DRAGON SOFTWARE: AN EASY APPROACH TO MOLECULAR DESCRIPTOR CALCULATIONS

Manuela Pavan, Roberto Todeschini, Viviana Consonni, 2006 .

A QSTR-Based Expert System to Predict Sweetness of Molecules

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2017, Front. Chem..

High-performance size-exclusion chromatographic behaviour of substituted benzoylpoly-L-lysines by principal component analysis and molecular dynamics simulation

Marco Orlandi, Viviana Consonni, Ezio Bolzacchini, 1998 .

Distances and Other Dissimilarity Measures in Chemometrics

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2015 .

QSAR study on the tropospheric degradation of organic compounds

Paola Gramatica, Roberto Todeschini, Viviana Consonni, 1999 .

A distance measure between models: a tool for similarity/diversity analysis of model populations

Manuela Pavan, Roberto Todeschini, Viviana Consonni, 2004 .

Towards Global QSAR Model Building for Acute Toxicity: Munro Database Case Study

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2014, International journal of molecular sciences.

Classification of multiway analytical data based on MOLMAP approach.

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2007, Analytica chimica acta.

Expert QSAR system for predicting the bioconcentration factor under the REACH regulation.

Roberto Todeschini, Marco Vighi, Viviana Consonni, 2016, Environmental research.

Matrix‐based Molecular Descriptors for Prospective Virtual Compound Screening

Roberto Todeschini, Petra Schneider, Gisbert Schneider, 2017, Molecular informatics.

In Silico Prediction of Cytochrome P450-Drug Interaction: QSARs for CYP3A4 and CYP2C9

Roberto Todeschini, Viviana Consonni, Francesca Grisoni, 2016, International journal of molecular sciences.

CAIMAN (Classification and Influence Matrix Analysis) : A new approach to the classification based on leverage-scaled functions

Manuela Pavan, Roberto Todeschini, Davide Ballabio, 2007 .

A new concept of higher-order similarity and the role of distance/similarity measures in local classification methods

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2016 .

Canonical Measure of Correlation (CMC) and Canonical Measure of Distance (CMD) between sets of data. Part 3. Variable selection in classification.

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2010, Analytica chimica acta.

Locally centred Mahalanobis distance: a new distance measure with salient features towards outlier detection.

Peter Filzmoser, Roberto Todeschini, Faizan Sahigara, 2013, Analytica chimica acta.

New QSAR Modelling Approach Based on Ranking Models by Genetic Algorithms - Variable Subset Selection (GA-VSS)

Manuela Pavan, Paola Gramatica, Roberto Todeschini, 2006 .

Quantitative structure–activity relationships to predict sweet and non-sweet tastes

Roberto Todeschini, Davide Ballabio, Viviana Consonni, 2016, Theoretical Chemistry Accounts.

A novel variable reduction method adapted from space-filling designs

Roberto Todeschini, M. Claeys-Bruno, Davide Ballabio, 2014 .

Relationships between apple texture and rheological parameters by means of multivariate analysis

Fabrizio Costa, Davide Ballabio, Viviana Consonni, 2012 .