Roberto Todeschini

Active 1989–2024

100
Papers
19,137
Citations
53
h-index
96
i10-index

Citations

Citations per year for Roberto Todeschini1983: 1 citations1985: 1 citations1988: 1 citations1990: 1 citations1992: 1 citations1993: 1 citations1994: 5 citations1995: 1 citations1996: 11 citations1997: 47 citations1998: 28 citations1999: 49 citations2000: 44 citations2001: 56 citations2002: 62 citations2003: 132 citations2004: 135 citations2005: 122 citations2006: 159 citations2007: 185 citations2008: 202 citations2009: 292 citations2010: 253 citations2011: 256 citations2012: 280 citations2013: 265 citations2014: 274 citations2015: 267 citations2016: 366 citations2017: 339 citations2018: 477 citations2019: 593 citations2020: 709 citations2021: 646 citations2022: 495 citations2023: 432 citations2024: 603 citations2025: 375 citations2026: 60 citations1984: no citations, so this year is not shown1986–1987: no citations, so these years are not shown1989: no citations, so this year is not shown1991: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 1,289 citing papers, 14.4% of this breakdownChina: 955 citing papers, 10.7% of this breakdownIndia: 496 citing papers, 5.5% of this breakdownItaly: 488 citing papers, 5.5% of this breakdownUnited Kingdom: 478 citing papers, 5.3% of this breakdownGermany: 425 citing papers, 4.7% of this breakdownSpain: 309 citing papers, 3.5% of this breakdownIran: 291 citing papers, 3.3% of this breakdownFrance: 225 citing papers, 2.5% of this breakdownSwitzerland: 183 citing papers, 2% of this breakdownCanada: 167 citing papers, 1.9% of this breakdownJapan: 164 citing papers, 1.8% of this breakdown
0%14.4%Other 38.9%

Fields

  • Computer Science58.1%
  • Mathematics7.8%
  • Biochemistry, Genetics and Molecular Biology7.7%
  • Chemistry5.4%
  • Medicine5.1%
  • Materials Science3.5%
  • Other12.4%

Topics

  • Computational Drug Discovery Methods24.5%
  • Machine Learning in Materials Science4.8%
  • Analytical Chemistry and Chromatography4%
  • Graph theory and applications3.2%
  • Metabolomics and Mass Spectrometry Studies2.8%
  • Protein Structure and Dynamics2.2%
  • Other58.5%

Coauthors

All papers

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  1. QSAR Modeling: Where Have You Been? Where Are You Going To?

    Authors: , , , , , , , , , , , , , , , , , , , - Journal of Medicinal Chemistry 2013 cited by 2,073

  2. Handbook of Molecular Descriptors

    Authors: , - Methods and principles in medicinal chemistry 2000 cited by 4,137

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

    Authors: , , , , , - Molecules 2012 cited by 608

  4. Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Antony J. Williams, Valery Tkachenko, Igor V. Tetko - Journal of Computer-Aided Molecular Design, J. Comput. Aided Mol. Des. 2011 cited by 687

  5. Multivariate comparison of classification performance measures

    Authors: , , - Chemometrics and Intelligent Laboratory Systems 2017 cited by 320

  6. Comments on the Definition of the Q2 Parameter for QSAR Validation

    Authors: , , - Journal of Chemical Information and Modeling, J. Chem. Inf. Model. 2009 cited by 582

  7. Virtual Computational Chemistry Laboratory - Design and Description

    Authors: , , , , , , , , , , , - Journal of Computer-Aided Molecular Design, J. Comput. Aided Mol. Des. 2005 cited by 1,501

  8. Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection

    Authors: , , , , , , , , , - Journal of Chemical Information and Modeling, J. Chem. Inf. Model. 2008 cited by 412

  9. CATMoS: Collaborative Acute Toxicity Modeling Suite

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Feng Gao, Jeffery M. Gearhart, Garett Goh, Jonathan M. Goodman, Francesca Grisoni, Chris Grulke, Thomas Härtung, Matthew Hirn, Pavel Karpov, Alexandru Korotcov, Giovanna J. Lavado, Michael S. Lawless, Xinhao Li, Thomas Luechtefeld, Filippo Lunghini, Giuseppe Felice Mangiatordi, Gilles Marcou, Dan H. Marsh, Todd M. Martin, Andrea Mauri, Eugene Muratov, Glenn J. Myatt, Ðắc-Trung Nguyễn, Orazio Nicolotti, Reine Note, Paritosh Pande, Amanda K. Parks, Tyler Peryea, Ahsan Habib Polash, Robert Ralló, Alessandra Roncaglioni, Craig Rowlands, Patricia Ruiz, Daniel P. Russo, Ahmed E Sayed, Risa Sayre, Timothy Sheils, Charles Siegel, Arthur C. Silva, Anton Simeonov, Sergey Sosnin, Noel Southall, Judy Strickland, Yun Tang, Brian J. Teppen, Igor V. Tetko, Dennis Thomas, Valery Tkachenko, Roberto Todeschini, Cosimo Toma, Ignacio J. Tripodi, Daniela Trisciuzzi, Alexander Tropsha, Alexandre Varnek, Kristijan Vuković, Zhongyu Wang, Liguo Wang, Katrina M. Waters, Andrew J. Wedlake, Sanjeeva J. Wijeyesakere, Dan Wilson, Zijun Xiao, Hongbin Yang, Gergely Zahoránszky-Köhalmi, Alexey Zakharov, Fagen F. Zhang, Zhen Zhang, Tongan Zhao, Hao Zhu, Kimberley M. Zorn and 2 more - Environmental Health Perspectives 2021 cited by 141

  10. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Patrik L. Andersson, Qingda Zang, Regina Politi, Richard D. Beger, Roberto Todeschini, Ruili Huang, Sherif S. Farag, Sine Abildgaard Rosenberg, Svetoslav Slavov, Xin Hu, Richard Judson - Environmental Health Perspectives 2016 cited by 372

  11. Similarity Coefficients for Binary Chemoinformatics Data: Overview and Extended Comparison Using Simulated and Real Data Sets

    Authors: , , , , , - Journal of Chemical Information and Modeling, J. Chem. Inf. Model. 2012 cited by 234

  12. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Giuseppe Felice Mangiatordi, Uko Maran, Gilles Marcou, Todd M. Martin, Eugene Muratov, Ðắc-Trung Nguyễn, Orazio Nicolotti, Nikolai Georgiev Nikolov, Ulf Norinder, Ester Papa, Michel Petitjean, Geven Piir, Pavel V. Pogodin, Vladimir Poroikov, Xianliang Qiao, Ann M. Richard, Alessandra Roncaglioni, Patricia Ruiz, Chetan Rupakheti, Sugunadevi Sakkiah, Alessandro Sangion, Karl‐Werner Schramm, Chandrabose Selvaraj, Imran Shah, Sulev Sild, Lixia Sun, Olivier Taboureau, Yun Tang, Igor V. Tetko, Roberto Todeschini, Weida Tong, Daniela Trisciuzzi, Alexander Tropsha, George A. Van Den Driessche, Alexandre Varnek, Zhongyu Wang, Eva Bay Wedebye, Antony Williams, Hong‐Bin Xie, Alexey Zakharov, Ziye Zheng, Richard Judson - Environmental Health Perspectives 2020 cited by 214

  13. Applicability Domains for Classification Problems: Benchmarking of Distance to Models for Ames Mutagenicity Set

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Alexandre Varnek, Volodymyr V. Prokopenko, Igor V. Tetko - Journal of Chemical Information and Modeling, J. Chem. Inf. Model. 2010 cited by 259

  14. DRAGON SOFTWARE: AN EASY APPROACH TO MOLECULAR DESCRIPTOR CALCULATIONS

    Authors: , , , , - 2006 cited by 508

  15. Classification-based machine learning approaches to predict the taste of molecules: A review

    Authors: , , , , - Food Research International 2023 cited by 39

  16. Impact of Molecular Descriptors on Computational Models

    Authors: , , - Methods in molecular biology 2018 cited by 73

  17. Molecular Descriptors

    Authors: , - Challenges and advances in computational chemistry and physics 2009 cited by 121

  18. Extended multivariate comparison of 68 cluster validity indices. A review

    Authors: , , , - Chemometrics and Intelligent Laboratory Systems 2024 cited by 39

  19. Quantitative Structure-Activity Relationship Models for Ready Biodegradability of Chemicals

    Authors: , , , , - Journal of Chemical Information and Modeling, J. Chem. Inf. Model. 2013 cited by 221

  20. Molecular Descriptors for Chemoinformatics : Volume I : Alphabetical Listing / Volume II : Appendices, References

    Authors: , - 2009 cited by 143

  21. A similarity-based QSAR model for predicting acute toxicity towards the fathead minnow (Pimephales promelas)

    Authors: , , , - SAR and QSAR in environmental research 2015 cited by 85

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

    Authors: , , , - Journal of Cheminformatics, J. Cheminformatics 2013 cited by 108

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

    Authors: , , , - Methods in molecular biology 2018 cited by 83

  24. Evaluation of model predictive ability by external validation techniques

    Authors: , , - Journal of Chemometrics 2010 cited by 362