World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
40
Citations
8100
World Ranking
7214
National Ranking
251

Overview

Davide Ballabio is affiliated with the University of Milano-Bicocca in Italy. Their research activity spans multiple fields primarily related to chemistry, with a strong focus on analytical chemistry and computational methods applied to chemical and biological data.

The main field of study for Ballabio is Chemistry, with a total of 34 publications. Subfields include Analytical Chemistry, Computational Theory and Mathematics, Molecular Biology, Spectroscopy, and Biomedical Engineering. This multidisciplinary background supports diverse research themes involving both experimental and computational approaches.

Key research topics covered in their published work consist of:

  • Computational Drug Discovery Methods
  • Spectroscopy and Chemometric Analyses
  • Analytical Chemistry and Chromatography
  • Advanced Chemical Sensor Technologies
  • Metabolomics and Mass Spectrometry Studies
  • Machine Learning in Materials Science
  • Spectroscopy Techniques in Biomedical and Chemical Research

They have contributed to publications in a variety of scientific venues. The most frequent venues for Ballabio's work include:

  • Chemometrics and Intelligent Laboratory Systems
  • Zenodo (CERN European Organization for Nuclear Research)
  • Environmental Health Perspectives
  • Molecules
  • Separations

Ballabio's recent scientific papers demonstrate a breadth of topics and collaboration. Some of the notable publications are:

  • CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity (2020) in Environmental Health Perspectives
  • CATMoS: Collaborative Acute Toxicity Modeling Suite (2021) in Environmental Health Perspectives
  • Geographical identification of Chianti red wine based on ICP-MS element composition (2020) in Food Chemistry
  • Self-Organizing Map and Relational Perspective Mapping for the Accurate Visualization of High-Dimensional Hyperspectral Data (2020) in Analytical Chemistry
  • A MATLAB toolbox for multivariate regression coupled with variable selection (2021) in Chemometrics and Intelligent Laboratory Systems

Their frequent co-authors reflect an active collaboration network including:

  • Viviana Consonni
  • Roberto Todeschini
  • Francesca Grisoni
  • Cecile Valsecchi
  • Fabio Gosetti

Best Publications

  • Classification tools in chemistry. Part 1: linear models. PLS-DA

    Davide Ballabio;Viviana Consonni

  • Comparison of different approaches to define the applicability domain of QSAR models.

    F Sahigara;K Mansouri;D Ballabio;A Mauri

  • Evaluation of model predictive ability by external validation techniques

    Viviana Consonni;Davide Ballabio;Roberto Todeschini

  • Multivariate comparison of classification performance measures

    Davide Ballabio;Francesca Grisoni;Francesca Grisoni;Roberto Todeschini

  • Quantitative structure-activity relationship models for ready biodegradability of chemicals.

    Kamel Mansouri;Tine Ringsted;Davide Ballabio;Roberto Todeschini

  • A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure

    Davide Ballabio

  • Evaluation of different storage conditions of extra virgin olive oils with an innovative recognition tool built by means of electronic nose and electronic tongue

    M. S. Cosio;D. Ballabio;S. Benedetti;Carmelina Gigliotti

  • Geographical origin and authentication of extra virgin olive oils by an electronic nose in combination with artificial neural networks

    Maria S. Cosio;Davide Ballabio;Simona Benedetti;Carmelina Gigliotti

  • Prediction of Italian red wine sensorial descriptors from electronic nose, electronic tongue and spectrophotometric measurements by means of Genetic Algorithm regression models

    S. Buratti;D. Ballabio;S. Benedetti;M.S. Cosio

  • CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity.

    Kamel Mansouri;Nicole Kleinstreuer;Ahmed M. Abdelaziz;Domenico Alberga

  • Particle size, chemical composition, seasons of the year and urban, rural or remote site origins as determinants of biological effects of particulate matter on pulmonary cells.

    M.G. Perrone;Maurizio Gualtieri;V. Consonni;L. Ferrero

  • A MATLAB toolbox for Self Organizing Maps and supervised neural network learning strategies

    Davide Ballabio;Mahdi Vasighi

  • The Kohonen and CP-ANN toolbox: A collection of MATLAB modules for Self Organizing Maps and Counterpropagation Artificial Neural Networks

    Davide Ballabio;Viviana Consonni;Roberto Todeschini

  • Multivariate Classification for Qualitative Analysis

    Davide Ballabio;Roberto Todeschini

  • CATMoS: Collaborative Acute Toxicity Modeling Suite.

    Kamel Mansouri;Agnes L. Karmaus;Jeremy Fitzpatrick;Grace Patlewicz

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

    Faizan Sahigara;Davide Ballabio;Roberto Todeschini;Viviana Consonni

  • Beware of Unreliable Q2! A Comparative Study of Regression Metrics for Predictivity Assessment of QSAR Models.

    Roberto Todeschini;Davide Ballabio;Francesca Grisoni

  • Amperometric electronic tongue for food analysis

    Matteo Scampicchio;Davide Ballabio;Alessandra Arecchi;Stella M. Cosio

  • A novel variable reduction method adapted from space-filling designs

    Davide Ballabio;Viviana Consonni;Andrea Mauri;Magalie Claeys-Bruno

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

    Roberto Todeschini;Davide Ballabio;Viviana Consonni;Faizan Sahigara

  • Classification of GC‐MS measurements of wines by combining data dimension reduction and variable selection techniques

    Davide Ballabio;Thomas Hjort Skov;Riccardo Leardi;Rasmus Bro

  • Genetic Algorithms for architecture optimisation of Counter-Propagation Artificial Neural Networks

    Davide Ballabio;Mahdi Vasighi;Viviana Consonni;Mohsen Kompany-Zareh

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

    Francesca Grisoni;Viviana Consonni;Davide Ballabio

  • Integrated QSAR Models to Predict Acute Oral Systemic Toxicity

    Davide Ballabio;Francesca Grisoni;Viviana Consonni;Roberto Todeschini

  • A QSTR-based expert system to predict sweetness of molecules

    Cristian Rojas;Roberto Todeschini;Davide Ballabio;Andrea Mauri

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

    R. Todeschini;D. Ballabio;V. Consonni;A. Mauri

  • Self-Organizing Map and Relational Perspective Mapping for the Accurate Visualization of High-Dimensional Hyperspectral Data.

    Wil Gardner;Wil Gardner;Ruqaya Maliki;Suzanne M. Cutts;Benjamin W. Muir

  • Development of models for predicting toxicity from sediment chemistry by partial least squares-discriminant analysis and counter-propagation artificial neural networks.

    Manuel Alvarez-Guerra;Davide Ballabio;José Manuel Amigo;Rasmus Bro

  • On the application of chemometrics for the study of acoustic-mechanical properties of crispy bakery products

    Laura Piazza;Jiabril Gigli;Davide Ballabio

Frequent Co-Authors

Roberto Todeschini
Roberto Todeschini University of Milano-Bicocca
Viviana Consonni
Viviana Consonni University of Milano-Bicocca
Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill
Igor V. Tetko
Igor V. Tetko Helmholtz Zentrum München
Rasmus Bro
Rasmus Bro University of Copenhagen
Alexander Tropsha
Alexander Tropsha University of North Carolina at Chapel Hill
Denis Fourches
Denis Fourches North Carolina State University
Alexandre Varnek
Alexandre Varnek University of Strasbourg
Sean Ekins
Sean Ekins University of Arizona
Thomas Hartung
Thomas Hartung Johns Hopkins University

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