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Chemistry

D-Index
48
Citations
9559
World Ranking
15139
National Ranking
843

Overview

John C. Dearden is affiliated with Liverpool John Moores University in the United Kingdom. Their research encompasses various areas within computer science, focusing notably on computational theory and mathematics.

Their publication record includes contributions to multiple fields, with key subfields including computational theory and mathematics, small animals, health, toxicology and mutagenesis, electrochemistry, and plant science.

The primary topics explored in their work include computational drug discovery methods, animal testing and alternatives, environmental toxicology and ecotoxicology, electrochemical analysis and applications, pesticide exposure and toxicity, as well as vitamin D research studies.

Recent papers authored or coauthored by John C. Dearden are as follows:

  • Prediction of Human Lethal Doses and Concentrations of MEIC Chemicals from Rodent LD50 Values: An Attempt to Make Some Reparation, 2021, Alternatives to Laboratory Animals
  • Effect of the structural factors of organic compounds on the acute toxicity toward Daphnia magna, 2020, SAR and QSAR in environmental research
  • Rodent LD50 Tests, 2020, International Journal of Quantitative Structure-Property Relationships
  • QSAR Modeling: Where Have You Been? Where Are You Going To?, 2020, UNC Libraries
  • Correlation between vitamin D levels, individual and socio-demographic characteristics and COVID-19 infection and death rates in 20 European countries: A modelling study, 2020, DOAJ (DOAJ: Directory of Open Access Journals)

Frequent coauthors in their research include:

  • Mark Hewitt
  • O.V. Tinkov
  • V.Y. Grigorev
  • Alexander N. Razdolsky
  • L.D. Grigoryeva

The venues where John C. Dearden has published more than once reflect the range of topics addressed in their work and include:

  • Alternatives to Laboratory Animals
  • SAR and QSAR in environmental research
  • International Journal of Quantitative Structure-Property Relationships
  • UNC Libraries
  • DOAJ (DOAJ: Directory of Open Access Journals)

Best Publications

  • QSAR Modeling: Where have you been? Where are you going to?

    Artem Cherkasov;Eugene N. Muratov;Eugene N. Muratov;Denis Fourches;Alexandre Varnek

  • How not to develop a quantitative structure–activity or structure–property relationship (QSAR/QSPR)

    J C Dearden;M T D Cronin;K L E Kaiser

  • The Measurement of Partition Coefficients

    John C. Dearden;Gaynor M. Bresnen

  • In silico prediction of drug toxicity.

    John C. Dearden

  • Quantitative structure-permeability relationships (QSPRs) for percutaneous absorption.

    G.P. Moss;J.C. Dearden;H. Patel;M.T.D. Cronin

  • The History and Development of Quantitative Structure-Activity Relationships (QSARs)

    John C. Dearden

  • 2-Heteroarylimino-5-benzylidene-4-thiazolidinones analogues of 2-thiazolylimino-5-benzylidene-4-thiazolidinones with antimicrobial activity: synthesis and structure-activity relationship.

    Paola Vicini;Athina Geronikaki;Matteo Incerti;Franca Zani

  • Investigation of the mechanism of flux across human skin in vitro by quantitative structure–permeability relationships

    M.T.D. Cronin;J.C. Dearden;G.P. Moss;G. Murray-Dickson

  • Design, synthesis, computational and biological evaluation of new anxiolytics.

    Athina Geronikaki;Eugeni Babaev;John Dearden;Wim Dehaen

  • Quantitative structure-property relationships for prediction of boiling point, vapor pressure, and melting point

    John C. Dearden

  • QSAR in Toxicology. 1. Prediction of Aquatic Toxicity

    Mark T. D. Cronin;John C. Dearden

  • Guidelines for developing and using quantitative structure-activity relationships.

    John D. Walker;Joanna Jaworska;Mike H. I. Comber;T. Wayne Schultz

  • The development and validation of expert systems for predicting toxicity : The report and recommendations of an ECVAM/ECB workshop (ECVAM Workshop 24)

    John C. Dearden;Martin D. Barratt;Romualdo Benigni;Douglas W. Bristol

  • In silico prediction of aqueous solubility

    John C Dearden

  • Partitioning and lipophilicity in quantitative structure-activity relationships.

    Unknown

  • QSAR study of the toxicity of benzoic acids to Vibrio fischeri, Daphnia magna and carp

    Y.H. Zhao;G.D. Ji;M.T.D. Cronin;J.C. Dearden

  • Structure-based classification of antibacterial activity.

    Mark T. D. Cronin;Aynur O. Aptula;John C. Dearden;Judith C. Duffy

  • In silico prediction of aqueous solubility: the solubility challenge.

    Mark Hewitt;Mark T. D. Cronin;Steven J. Enoch;Judith C. Madden

  • Linear QSAR regression models for the prediction of bioconcentration factors by physicochemical properties and structural theoretical molecular descriptors

    E. Papa;J.C. Dearden;P. Gramatica

  • Design of new cognition enhancers: from computer prediction to synthesis and biological evaluation.

    Athina A. Geronikaki;John C. Dearden;Dmitrii Filimonov;Irina Galaeva

  • QSAR Study of the Toxicity of Nitrobenzenes to Tetrahymena pyriformis

    John C. Dearden;Mark T. D. Cronin;T. Wayne Schultz;David T. Lin

  • QSAR studies of comparative toxicity in aquatic organisms.

    M.T.D. Cronin;J.C. Dearden;A.J. Dobbs

Frequent Co-Authors

Mark T. D. Cronin
Mark T. D. Cronin Liverpool John Moores University
Vladimir Poroikov
Vladimir Poroikov Institute of Business & Medical Careers
David W. Roberts
David W. Roberts Liverpool John Moores University
Gerrit Schüürmann
Gerrit Schüürmann Helmholtz Centre for Environmental Research
Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill
Denis Fourches
Denis Fourches North Carolina State University
Johann Gasteiger
Johann Gasteiger University of Erlangen-Nuremberg
Viviana Consonni
Viviana Consonni University of Milano-Bicocca
Alexander Tropsha
Alexander Tropsha University of North Carolina at Chapel Hill
Ian T. Cousins
Ian T. Cousins Stockholm University

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