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D-Index & Metrics

Engineering and Technology

D-Index
36
Citations
4555
World Ranking
8777
National Ranking
207

Overview

Dragos Horvath is affiliated with the University of Strasbourg in France. Their research spans several scientific domains with a focus on the intersection of biochemistry, molecular biology, and computer science.

The main fields of study represented in their work include:

  • Biochemistry, Genetics and Molecular Biology
  • Computer Science

Within these broader fields, they have explored various subfields such as:

  • Molecular Biology
  • Computational Theory and Mathematics
  • Pharmacology
  • Biomedical Engineering
  • Materials Chemistry

Dragos Horvath's research topics cover a diverse range of areas, including:

  • Computational Drug Discovery Methods
  • Microbial Natural Products and Biosynthesis
  • Machine Learning in Materials Science
  • Chemical Synthesis and Analysis
  • Metabolomics and Mass Spectrometry Studies
  • Analytical Chemistry and Chromatography
  • Innovative Microfluidic and Catalytic Techniques Innovation

They have an extensive publication record, frequently contributing to journals such as:

  • Journal of Chemical Information and Modeling
  • Molecular Informatics
  • Zenodo (CERN European Organization for Nuclear Research)
  • Chemistry - A European Journal
  • bioRxiv (Cold Spring Harbor Laboratory)

Selected recent papers authored or co-authored by Dragos Horvath include:

  • CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity, 2020, Environmental Health Perspectives
  • A Close-up Look at the Chemical Space of Commercially Available Building Blocks for Medicinal Chemistry, 2021, Journal of Chemical Information and Modeling
  • Discovery of novel chemical reactions by deep generative recurrent neural network, 2021, Scientific Reports
  • Computational screening methodology identifies effective solvents for CO2 capture, 2022, Communications Chemistry
  • Will we ever be able to accurately predict solubility?, 2024, Scientific Data

Their collaborative network includes frequent co-authors such as:

  • Alexandre Varnek
  • Gilles Marcou
  • Alexey A. Orlov
  • Yuliana Zabolotna
  • Arkadii Lin

Best Publications

  • CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Kamel Mansouri;Ahmed Abdelaziz;Aleksandra Rybacka;Alessandra Roncaglioni

  • Applicability domains for classification problems: Benchmarking of distance to models for Ames mutagenicity set.

    Iurii Sushko;Sergii Novotarskyi;Robert Körner;Anil Kumar Pandey

  • ISIDA - Platform for Virtual Screening Based on Fragment and Pharmacophoric Descriptors

    Alexandre Varnek;Denis Fourches;Dragos Horvath;Olga Klimchuk

  • CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity.

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

  • De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping

    Boris Sattarov;Igor I. Baskin;Dragos Horvath;Gilles Marcou

  • ISIDA Property‐Labelled Fragment Descriptors

    Fiorella Ruggiu;Gilles Marcou;Alexandre Varnek;Dragos Horvath

  • Generative Topographic Mapping (GTM): Universal Tool for Data Visualization, Structure-Activity Modeling and Dataset Comparison.

    N. Kireeva;I. I. Baskin;I. I. Baskin;H. A. Gaspar;D. Horvath

  • Chemical data visualization and analysis with incremental generative topographic mapping: big data challenge.

    Héléna A. Gaspar;Igor I. Baskin;Igor I. Baskin;Igor I. Baskin;Gilles Marcou;Dragos Horvath

  • Pharmacophore-based virtual screening.

    Dragos Horvath

  • Predicting the Predictability: A Unified Approach to the Applicability Domain Problem of QSAR Models

    Unknown

  • Expert System for Predicting Reaction Conditions: The Michael Reaction Case

    G. Marcou;J. Aires de Sousa;D. A. R. S. Latino;A. de Luca

  • GTM-Based QSAR Models and Their Applicability Domains.

    H. A. Gaspar;I. I. Baskin;I. I. Baskin;I. I. Baskin;G. Marcou;D. Horvath

  • Discovery of novel chemical reactions by deep generative recurrent neural network

    William Bort;Igor I. Baskin;Igor I. Baskin;Igor I. Baskin;Timur Gimadiev;Artem Mukanov

  • Generative topographic mapping-based classification models and their applicability domain: application to the biopharmaceutics Drug Disposition Classification System (BDDCS).

    Héléna A. Gaspar;Gilles Marcou;Dragos Horvath;Alban Arault

  • An Evolutionary Optimizer of libsvm Models

    Dragos Horvath;J. B. Brown;Gilles Marcou;Alexandre Varnek

  • Computational screening methodology identifies effective solvents for CO2 capture

    Unknown

  • A parallel hybrid genetic algorithm for protein structure prediction on the computational grid

    A. A. Tantar;N. Melab;E. G. Talbi;B. Parent

  • Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins

    Chisa Higuchi;Chisa Higuchi;Dragos Horvath;Gilles Marcou;Kazunari Yoshizawa

  • Interpretability of SAR/QSAR Models of any Complexity by Atomic Contributions.

    Gilles Marcou;Dragos Horvath;V. Solov'ev;A. Arrault

  • Electrochemical properties of substituted 2-methyl-1,4-naphthoquinones: redox behavior predictions.

    Mourad Elhabiri;Pavel Sidorov;Pavel Sidorov;Elena Cesar‐Rodo;Gilles Marcou

  • Mapping of the Available Chemical Space versus the Chemical Universe of Lead-Like Compounds.

    Arkadii Lin;Dragos Horvath;Valentina Afonina;Valentina Afonina;Gilles Marcou

  • S4MPLE—Sampler for Multiple Protein-Ligand Entities: Methodology and Rigid-Site Docking Benchmarking

    Laurent Hoffer;Camelia Chira;Gilles Marcou;Alexandre Varnek

  • Mining chemical reactions using neighborhood behavior and condensed graphs of reactions approaches.

    Aurélie de Luca;Dragos Horvath;Gilles Marcou;Vitaly P. Solov'ev;Vitaly P. Solov'ev

  • Predictive Models for Kinetic Parameters of Cycloaddition Reactions

    Marta Glavatskikh;Marta Glavatskikh;Timur Madzhidov;Dragos Horvath;Ramil Nugmanov

  • Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression.

    Dragos Horvath;Gilles Marcou;Alexandre Varnek;Shilva Kayastha;Shilva Kayastha

  • Generative topographic mapping in drug design.

    Dragos Horvath;Gilles Marcou;Alexandre Varnek

  • Models for Identification of Erroneous Atom-to-Atom Mapping of Reactions Performed by Automated Algorithms

    Christophe Muller;Gilles Marcou;Dragos Horvath;João Aires-de-Sousa

  • Chemoinformatics-Driven Design of New Physical Solvents for Selective CO2 Absorption.

    Alexey A. Orlov;Daryna Yu. Demenko;Charles Bignaud;Alain Valtz

  • Chemography: Searching for Hidden Treasures.

    Yuliana Zabolotna;Arkadii I. Lin;Dragos Horvath;Gilles Marcou

  • Using self-organizing maps to accelerate similarity search

    Fanny Bonachera;Gilles Marcou;Natalia Kireeva;Alexandre Varnek

Frequent Co-Authors

Alexandre Varnek
Alexandre Varnek University of Strasbourg
Denis Fourches
Denis Fourches North Carolina State University
Igor V. Tetko
Igor V. Tetko Helmholtz Zentrum München
Roberto Todeschini
Roberto Todeschini University of Milano-Bicocca
Jürgen Bajorath
Jürgen Bajorath University of Bonn
Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill
Vladimir Poroikov
Vladimir Poroikov Institute of Business & Medical Careers
Ruili Huang
Ruili Huang National Institutes of Health
Alexander Tropsha
Alexander Tropsha University of North Carolina at Chapel Hill
Jacques Haiech
Jacques Haiech University of Strasbourg

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