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Emilio Benfenati

Istituto di Ricerche Farmacologiche Mario NegriIN
ORCID0000-0002-3976-5989
h-index
65

via OpenAlex

Citations
20,219

via OpenAlex

Publications
732

About

Emilio Benfenati is a researcher at Istituto di Ricerche Farmacologiche Mario Negri. He has a long-standing focus on QSAR modeling and ecotoxicology, with over 50 publications spanning four decades from 1970 to 2020. His work explores the prediction of chemical toxicity to various organisms and ecosystems, including aquatic solubility, genotoxicity, and carcinogenicity.

Research areas

  • Quantitative structure–activity relationship
  • Chemistry
  • Computer science
  • Biology
  • Organic chemistry

Publications (732)

Sorted by most cited.

  1. CAESAR models for developmental toxicity

    2010

    View DOI
    1,537 cites
  2. Alternative (non-animal) methods for cosmetics testing: current status and future prospects—2010

    2011

    View DOI
    575 cites
  3. Green Chemistry in the Synthesis of Pharmaceuticals

    2021

    View DOI
    508 cites
  4. Guidance on the use of the weight of evidence approach in scientific assessments

    2017

    View DOI
    407 cites
  5. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    2016

    View DOI
    366 cites
  6. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

    2020

    View DOI
    208 cites
  7. SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data

    2019

    View DOI
    196 cites
  8. Genotoxicity of metal oxide nanomaterials: review of recent data and discussion of possible mechanisms

    2014

    View DOI
    191 cites
  9. A European perspective on alternatives to animal testing for environmental hazard identification and risk assessment

    2013

    View DOI
    179 cites
  10. Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction

    2013

    View DOI
    169 cites
  11. A combined approach to investigate the toxicity of an industrial landfill’s leachate: Chemical analyses, risk assessment and in vitro assays

    2011

    View DOI
    158 cites
  12. Ecotoxicological assessment of pharmaceuticals and personal care products using predictive toxicology approaches

    2020

    View DOI
    149 cites
  13. Exposure to PFOA and PFOS and fetal growth: a critical merging of toxicological and epidemiological data

    2017

    View DOI
    145 cites
  14. In vivo exposure of carp to graded concentrations of bisphenol A

    2007

    View DOI
    145 cites
  15. QSAR as a random event: Modeling of nanoparticles uptake in PaCa2 cancer cells

    2013

    View DOI
    142 cites
  16. CATMoS: Collaborative Acute Toxicity Modeling Suite

    2021

    View DOI
    137 cites
  17. New public QSAR model for carcinogenicity

    2010

    View DOI
    135 cites
  18. VEGA-QSAR: AI Inside a Platform for Predictive Toxicology.

    2013

    131 cites
  19. Comparison of<i>in silico</i>tools for evaluating rat oral acute toxicity

    2015

    View DOI
    126 cites
  20. Aquatic toxicity of several textile dye formulations: Acute and chronic assays with Daphnia magna and Raphidocelis subcapitata

    2017

    View DOI
    125 cites
  21. Predictive Models for Carcinogenicity and Mutagenicity: Frameworks, State-of-the-Art, and Perspectives

    2009

    View DOI
    122 cites
  22. Androgenic and antiandrogenic activities in water and sediment samples from the river Lambro, Italy, detected by yeast androgen screen and chemical analyses

    2007

    View DOI
    121 cites
  23. Interpretation of Quantitative Structure−Property and −Activity Relationships

    2001

    View DOI
    113 cites
  24. A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)

    2008

    View DOI
    112 cites
  25. The Expanding Role of Predictive Toxicology: An Update on the (Q)SAR Models for Mutagens and Carcinogens

    2007

    View DOI
    108 cites
  26. Guidance Document on Scientific criteria for grouping chemicals into assessment groups for human risk assessment of combined exposure to multiple chemicals

    2021

    View DOI
    106 cites
  27. In Silico Methods for Predicting Drug Toxicity

    2016

    View DOI
    105 cites
  28. In silico methods to predict drug toxicity

    2013

    View DOI
    105 cites
  29. Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli

    2012

    View DOI
    104 cites
  30. Predicting logP of pesticides using different software

    2003

    View DOI
    104 cites
  31. Comparison of In Silico Models for Prediction of Mutagenicity

    2013

    View DOI
    103 cites
  32. A generalizable definition of chemical similarity for read-across

    2014

    View DOI
    101 cites
  33. CORAL: Quantitative structure–activity relationship models for estimating toxicity of organic compounds in rats

    2011

    View DOI
    101 cites
  34. Volatile organic compounds produced during the aerobic biological processing of municipal solid waste in a pilot plant

    2004

    View DOI
    100 cites
  35. Computational predictive programs (expert systems) in toxicology

    1997

    View DOI
    98 cites
  36. Towards a systematic use of effect biomarkers in population and occupational biomonitoring

    2020

    View DOI
    97 cites
  37. Screening of endocrine-disrupting phenols, herbicides, steroid estrogens, and estrogenicity in drinking water from the waterworks of 35 Italian cities and from PET-bottled mineral water

    2012

    View DOI
    97 cites
  38. Estrogenicity profile and estrogenic compounds determined in river sediments by chemical analysis, ELISA and yeast assays

    2008

    View DOI
    92 cites
  39. Assessment and validation of the CAESAR predictive model for bioconcentration factor (BCF) in fish

    2010

    View DOI
    89 cites
  40. Ecotoxicological QSAR modeling of endocrine disruptor chemicals

    Journal of Hazardous Materials1970journal article

    View DOI
    83 cites
  41. REACH and in silico methods: an attractive opportunity for medicinal chemists

    2014

    View DOI
    82 cites
  42. Safer chemicals using less animals: kick-off of the European ONTOX project

    2021

    View DOI
    81 cites
  43. Structures of Endocrine-Disrupting Chemicals Determine Binding to and Activation of the Estrogen Receptor α and Androgen Receptor

    2020

    View DOI
    78 cites
  44. Predictive Carcinogenicity:  A Model for Aromatic Compounds, with Nitrogen-Containing Substituents, Based on Molecular Descriptors Using an Artificial Neural Network

    1999

    View DOI
    77 cites
  45. Sterols in sediment samples from Venice Lagoon, Italy

    1996

    View DOI
    77 cites
  46. QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis

    2018

    View DOI
    76 cites
  47. ToxRead: A tool to assist in read across and its use to assess mutagenicity of chemicals

    2014

    View DOI
    75 cites
  48. Analysis of some pesticides in water samples using solid-phase microextraction–gas chromatography with different mass spectrometric techniques

    1999

    View DOI
    75 cites
  49. The way forward for assessing the human health safety of cosmetics in the EU - Workshop proceedings

    2020

    View DOI
    73 cites
  50. Evaluation of QSAR Models for the Prediction of Ames Genotoxicity: A Retrospective Exercise on the Chemical Substances Registered Under the EU REACH Regulation

    2014

    View DOI
    73 cites
  51. Homology Modeling of the Human P-glycoprotein (ABCB1) and Insights into Ligand Binding through Molecular Docking Studies

    2020

    View DOI
    70 cites
  52. Computational drug repurposing: approaches, evaluation of in silico resources and case studies

    2025

    View DOI
    69 cites
  53. Predicting acute contact toxicity of pesticides in honeybees (Apis mellifera) through a k-nearest neighbor model

    2016

    View DOI
    69 cites
  54. QSAR models for predicting acute toxicity of pesticides in rainbow trout using the CORAL software and EFSA’s OpenFoodTox database

    2017

    View DOI
    67 cites
  55. Developing human biomonitoring as a 21st century toolbox within the European exposure science strategy 2020–2030

    2022

    View DOI
    66 cites
  56. CORAL: QSAR modeling of toxicity of organic chemicals towards Daphnia magna

    2011

    View DOI
    66 cites
  57. PCDD/Fs and PCBs in ambient air in a highly industrialized city in Northern Italy

    2012

    View DOI
    65 cites
  58. CORAL: Building up the model for bioconcentration factor and defining it’s applicability domain

    2011

    View DOI
    65 cites
  59. Increased concentrations of nitrophenols in leaves from a damaged forestal site

    1999

    View DOI
    65 cites
  60. EFSA’s OpenFoodTox: An open source toxicological database on chemicals in food and feed and its future developments

    2020

    View DOI
    64 cites
  61. Patterns and Sources of Polychlorinated Dibenzo-<i>p</i>-dioxins and Dibenzofurans in Sediments from the Venice Lagoon, Italy

    1997

    View DOI
    63 cites
  62. In silico models for predicting ready biodegradability under REACH: A comparative study

    2013

    View DOI
    60 cites
  63. Comparison of SMILES and molecular graphs as the representation of the molecular structure for QSAR analysis for mutagenic potential of polyaromatic amines

    2011

    View DOI
    60 cites
  64. Structures of Endocrine-Disrupting Chemicals Correlate with the Activation of 12 Classic Nuclear Receptors

    2021

    View DOI
    59 cites
  65. QSAR Model for Predicting Pesticide Aquatic Toxicity

    2005

    View DOI
    59 cites
  66. Acute phytotoxicity of seven metals alone and in mixture: Are Italian soil threshold concentrations suitable for plant protection?

    2015

    View DOI
    58 cites
  67. SMILES as an alternative to the graph in QSAR modelling of bee toxicity

    2007

    View DOI
    57 cites
  68. Description of the Electronic Structure of Organic Chemicals Using Semiempirical and Ab Initio Methods for Development of Toxicological QSARs

    2004

    View DOI
    57 cites
  69. Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: The bioconcentration factor (BCF)

    2015

    View DOI
    56 cites
  70. Meta-analysis of toxicity and teratogenicity of 133 chemicals from zebrafish developmental toxicity studies

    2013

    View DOI
    56 cites
  71. The acceptance of in silicomodels for REACH: Requirements, barriers, and perspectives

    2011

    View DOI
    56 cites
  72. SMILES in QSPR/QSAR Modeling: Results and Perspectives

    2007

    View DOI
    55 cites
  73. Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study

    2006

    View DOI
    54 cites
  74. SMILES‐based optimal descriptors: QSAR analysis of fullerene‐based HIV‐1 PR inhibitors by means of balance of correlations

    2009

    View DOI
    53 cites
  75. Investigating the Estrogenic Risk Along the River Po and Its Intermediate Section

    2006

    View DOI
    53 cites
  76. Integrating in silico models to enhance predictivity for developmental toxicity

    2016

    View DOI
    52 cites
  77. VOC exposures in California early childhood education environments

    2016

    View DOI
    51 cites
  78. An alternative QSAR-based approach for predicting the bioconcentration factor for regulatory purposes

    2014

    View DOI
    51 cites
  79. The Importance of Scaling in Data Mining for Toxicity Prediction

    2002

    View DOI
    51 cites
  80. Comparison of<i>in silico</i>models for prediction of<i>Daphnia magna</i>acute toxicity

    2014

    View DOI
    50 cites
  81. A comparative survey of chemistry-driven in silico methods to identify hazardous substances under REACH

    2013

    View DOI
    50 cites
  82. Modeling Toxicity by Using Supervised Kohonen Neural Networks

    2003

    View DOI
    50 cites
  83. The VEGAHUB Platform: The Philosophy and the Tools

    2022

    View DOI
    49 cites
  84. Polychlorinated dibenzo-p-dioxins (PCDD) and polychlorinated dibenzofurans (PCDF) in emissions from an urban incineratop. 1. Average and peak values

    1982

    View DOI
    49 cites
  85. Human biomonitoring and toxicokinetics as key building blocks for next generation risk assessment

    2024

    View DOI
    48 cites
  86. Binary classification models for endocrine disrupter effects mediated through the estrogen receptor

    2008

    View DOI
    48 cites
  87. PCDD, PCDF, PCB, PAH, cadmium and lead in roadside soil: relationship between road distance and concentration

    1992

    View DOI
    48 cites
  88. Physicochemical and Analytical Characteristics ofAmiodarone

    1984

    View DOI
    48 cites
  89. In Silico Methods for Predicting Drug Toxicity

    2022

    View DOI
    47 cites
  90. Directions in QSAR Modeling for Regulatory Uses in OECD Member Countries, EU and in Russia

    2008

    View DOI
    47 cites
  91. Machine learning - based q-RASAR modeling to predict acute contact toxicity of binary organic pesticide mixtures in honey bees

    2023

    View DOI
    46 cites
  92. New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments

    2021

    View DOI
    46 cites
  93. Integrated in silico strategy for PBT assessment and prioritization under REACH

    2016

    View DOI
    46 cites
  94. Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data

    2015

    View DOI
    46 cites
  95. Nano-QSAR: Model of mutagenicity of fullerene as a mathematical function of different conditions

    2015

    View DOI
    46 cites
  96. QSAR model for predicting cell viability of human embryonic kidney cells exposed to SiO2 nanoparticles

    2015

    View DOI
    46 cites
  97. Individual breast milk consumption and exposure to PCBs and PCDD/Fs in Hungarian infants: A time-course analysis of the first three months of lactation

    2013

    View DOI
    46 cites
  98. Co-evolutions of correlations for QSAR of toxicity of organometallic and inorganic substances: An unexpected good prediction based on a model that seems untrustworthy

    2011

    View DOI
    46 cites
  99. Additive SMILES-based optimal descriptors in QSAR modelling bee toxicity: Using rare SMILES attributes to define the applicability domain

    2008

    View DOI
    46 cites
  100. “De novo” synthesis of PCDD, PCDF, PCB, PCN and PAH in a pilot incinerator

    1991

    View DOI
    46 cites
  101. Comparison of genistein metabolism in rats and humans using liver microsomes and hepatocytes

    2007

    View DOI
    45 cites
  102. Comparative studies of the leachate of an industrial landfill by gas chromatography–mass spectrometry, liquid chromatography–nuclear magnetic resonance and liquid chromatography–mass spectrometry

    1999

    View DOI
    45 cites
  103. 45 cites
  104. Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure–activity relationship (q-RASAR) with the application of machine learning

    2024

    View DOI
    44 cites
  105. Optimal nano-descriptors as translators of eclectic data into prediction of the cell membrane damage by means of nano metal-oxides

    2014

    View DOI
    44 cites
  106. A new in silico classification model for ready biodegradability, based on molecular fragments

    2014

    View DOI
    44 cites
  107. QSAR modeling of measured binding affinity for fullerene-based HIV-1 PR inhibitors by CORAL

    2010

    View DOI
    44 cites
  108. 44 cites
  109. Exploring QSAR modeling of toxicity of chemicals on earthworm

    Ecotoxicology and Environmental Safety1970journal article

    View DOI
    44 cites
  110. QSAR models for soil ecotoxicity: Development and validation of models to predict reproductive toxicity of organic chemicals in the collembola Folsomia candida

    2021

    View DOI
    43 cites
  111. The ToxBank Data Warehouse: Supporting the Replacement of In Vivo Repeated Dose Systemic Toxicity Testing

    2013

    View DOI
    43 cites
  112. Quantitative consensus of bioaccumulation models for integrated testing strategies

    2012

    View DOI
    43 cites
  113. SMILES-based optimal descriptors: QSAR modeling of carcinogenicity by balance of correlations with ideal slopes

    2010

    View DOI
    43 cites
  114. Comparing <i>In Vivo</i> , <i>In Vitro</i> and <i>In Silico</i> Methods and Integrated Strategies for Chemical Assessment: Problems and Prospects

    2010

    View DOI
    43 cites
  115. QSAR models for Daphnia toxicity of pesticides based on combinations of topological parameters of molecular structures

    2005

    View DOI
    43 cites
  116. QSAR model as a random event: A case of rat toxicity

    2015

    View DOI
    42 cites
  117. <scp>coral</scp> Software: QSAR for Anticancer Agents

    2011

    View DOI
    42 cites
  118. Additive SMILES-Based Carcinogenicity Models: Probabilistic Principles in the Search for Robust Predictions

    2009

    View DOI
    42 cites
  119. QSAR in Ecotoxicity:  An Overview of Modern Classification Techniques

    2003

    View DOI
    41 cites
  120. Screening of 21 pesticides in water by single extraction with C18 silica bonded phase columns and HRGC-MS

    1988

    View DOI
    41 cites
  121. The application of new HARD-descriptor available from the CORAL software to building up NOAEL models

    2017

    View DOI
    40 cites
  122. In Silico Models for Repeated-Dose Toxicity (RDT): Prediction of the No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) for Drugs

    2016

    View DOI
    40 cites
  123. In silico-aided prediction of biological properties of chemicals: oestrogen receptor-mediated effects

    2007

    View DOI
    40 cites
  124. Predicting persistence in the sediment compartment with a new automatic software based on the k-Nearest Neighbor (k-NN) algorithm

    2015

    View DOI
    39 cites
  125. Chemical characterization and ecotoxicity of three soil foaming agents used in mechanized tunneling

    2015

    View DOI
    39 cites
  126. Using toxicological evidence from QSAR models in practice

    2013

    View DOI
    39 cites
  127. Could deep learning in neural networks improve the QSAR models?

    SAR and QSAR in Environmental Research1970journal article

    View DOI
    39 cites
  128. Integrate mechanistic evidence from new approach methodologies (NAMs) into a read-across assessment to characterise trends in shared mode of action

    2021

    View DOI
    38 cites
  129. CORAL: QSPR model of water solubility based on local and global SMILES attributes

    2012

    View DOI
    38 cites
  130. 38 cites
  131. Docking-Based Classification Models for Exploratory Toxicology Studies on High-Quality Estrogenic Experimental Data

    2015

    View DOI
    37 cites
  132. Coral: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical

    2012

    View DOI
    37 cites
  133. Data Quality Assessment for In Silico Methods: A Survey of Approaches and Needs

    2010

    View DOI
    37 cites
  134. The proposal of architecture for chemical splitting to optimize QSAR models for aquatic toxicity

    2008

    View DOI
    37 cites
  135. Emerging organic contaminants in leachates from industrial waste landfills and industrial effluent

    2003

    View DOI
    37 cites
  136. Ligand-based prediction of hERG-mediated cardiotoxicity based on the integration of different machine learning techniques

    2022

    View DOI
    36 cites
  137. PCDD/Fs in ambient air in north-east Italy: The role of a MSWI inside an industrial area

    2009

    View DOI
    36 cites
  138. Additive InChI-based optimal descriptors: QSPR modeling of fullerene C 60 solubility in organic solvents

    2009

    View DOI
    36 cites
  139. Comparative Quantitative Structure–Activity–Activity Relationships for Toxicity to <i>Tetrahymena pyriformis</i> and <i>Pimephales promelas</i>

    2007

    View DOI
    35 cites
  140. Combining Unsupervised and Supervised Artificial Neural Networks to PredictAquatic Toxicity

    2004

    View DOI
    35 cites
  141. Prediction of the Neurotoxic Potential of Chemicals Based on Modelling of Molecular Initiating Events Upstream of the Adverse Outcome Pathways of (Developmental) Neurotoxicity

    2022

    View DOI
    34 cites
  142. Ecotoxicological effects of atmospheric particulate produced by braking systems on aquatic and edaphic organisms

    2020

    View DOI
    34 cites
  143. QSAR models for biocides: The example of the prediction of <i>Daphnia magna</i> acute toxicity

    2020

    View DOI
    34 cites
  144. A knowledge-based expert rule system for predicting mutagenicity (Ames test) of aromatic amines and azo compounds

    2016

    View DOI
    34 cites
  145. New Quantitative Structure–Activity Relationship Models Improve Predictability of Ames Mutagenicity for Aromatic Azo Compounds

    2016

    View DOI
    34 cites
  146. Comparison between bioconcentration factor (BCF) data provided by industry to the European Chemicals Agency (ECHA) and data derived from QSAR models

    2015

    View DOI
    34 cites
  147. Integration of QSAR models for bioconcentration suitable for REACH

    2013

    View DOI
    34 cites
  148. CORAL: QSPR models for solubility of [C60] and [C70] fullerene derivatives

    2010

    View DOI
    34 cites
  149. A QSAR Study of Avian Oral Toxicity using Support Vector Machines and Genetic Algorithms

    2006

    View DOI
    34 cites
  150. Accelerated solvent extraction then liquid chromatography coupled with mass spectrometry for determination of 4-t-octylphenol, 4-nonylphenols, and bisphenol A in fish liver

    2002

    View DOI
    34 cites
  151. Fractionation and toxicity evaluation of waste waters

    2000

    View DOI
    34 cites
  152. QSAR modeling of endpoints for peptides which is based on representation of the molecular structure by a sequence of amino acids

    2012

    View DOI
    33 cites
  153. Analysis of the co-evolutions of correlations as a tool for QSAR-modeling of carcinogenicity: an unexpected good prediction based on a model that seems untrustworthy

    2010

    View DOI
    33 cites
  154. Factors Influencing Predictive Models for Toxicology

    2001

    View DOI
    33 cites
  155. The VEGA Tool to Check the Applicability Domain Gives Greater Confidence in the Prediction of In Silico Models

    2023

    View DOI
    32 cites
  156. A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts

    2016

    View DOI
    32 cites
  157. A new integrated in silico strategy for the assessment and prioritization of persistence of chemicals under REACH

    2016

    View DOI
    32 cites
  158. QSAR models for ACE-inhibitor activity of tri-peptides based on representation of the molecular structure by graph of atomic orbitals and SMILES

    2012

    View DOI
    32 cites
  159. The CAESAR project for in silico models for the REACH legislation

    2010

    View DOI
    32 cites
  160. A GC-MS method for the analysis of fecal and plant sterols in sediment samples

    1994

    View DOI
    32 cites
  161. CORAL: Building up QSAR models for the chromosome aberration test

    Saudi Journal of Biological Sciences1970journal article

    View DOI
    32 cites
  162. Patent Toxicity

    2021

    View DOI
    31 cites
  163. New clues on carcinogenicity-related substructures derived from mining two large datasets of chemical compounds

    2016

    View DOI
    31 cites
  164. Quasi-SMILES as a tool to utilize eclectic data for predicting the behavior of nanomaterials

    2016

    View DOI
    31 cites
  165. Concentrations of PCDD/PCDF in soil close to a secondary aluminum smelter

    2011

    View DOI
    31 cites
  166. Migration of vinyl chloride into PVC-bottled drinking-water assessed by gas chromatography-mass spectrometry

    1991

    View DOI
    31 cites
  167. Evaluation of QSAR models for predicting the partition coefficient (logP) of chemicals under the REACH regulation

    2015

    View DOI
    30 cites
  168. Chemical-based risk assessment and in vitro models of human health effects induced by organic pollutants in soils from the Olona valley

    2013

    View DOI
    30 cites
  169. CORAL: Monte Carlo Method as a Tool for the Prediction of the Bioconcentration Factor of Industrial Pollutants

    2012

    View DOI
    30 cites
  170. Coral: QSAR models for acute toxicity in fathead minnow (<i>Pimephales promelas</i>)

    2012

    View DOI
    30 cites
  171. Comparison and Possible Use of<i>In Silico</i>Tools for Carcinogenicity Within REACH Legislation

    2011

    View DOI
    30 cites
  172. Mining toxicity structural alerts from SMILES: A new way to derive Structure Activity Relationships

    2011

    View DOI
    30 cites
  173. A new bioconcentration factor model based on SMILES and indices of presence of atoms

    2010

    View DOI
    30 cites
  174. QSPR modeling for enthalpies of formation of organometallic compounds by means of SMILES-based optimal descriptors

    2008

    View DOI
    30 cites
  175. Predicting toxicity through computers: a changing world

    2007

    View DOI
    30 cites
  176. Tuning Neural and Fuzzy-Neural Networks for Toxicity Modeling

    2003

    View DOI
    30 cites
  177. Zebrafish AC modelling: (Q)SAR models to predict developmental toxicity in zebrafish embryo

    2020

    View DOI
    29 cites
  178. Optimal descriptor as a translator of eclectic information into the prediction of membrane damage: The case of a group of ZnO and TiO2 nanoparticles

    2014

    View DOI
    29 cites
  179. QSAR models of quail dietary toxicity based on the graph of atomic orbitals

    2006

    View DOI
    29 cites
  180. QSAR modelling of aldehyde toxicity by means of optimisation of correlation weights of nearest neighbouring codes

    2004

    View DOI
    29 cites
  181. Concentrations of PCDD and PCDF in different points of a modern refuse incinerator

    1990

    View DOI
    29 cites
  182. QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors

    2020

    View DOI
    28 cites
  183. QSAR model for pesticides toxicity to Rainbow Trout based on “ideal correlations”

    2020

    View DOI
    28 cites
  184. Methodology of aiQSAR: a group-specific approach to QSAR modelling

    2019

    View DOI
    28 cites
  185. (Q)SAR tools for priority setting: A case study with printed paper and board food contact material substances

    2017

    View DOI
    28 cites
  186. SMILES-based QSAR Approaches for Carcinogenicity and Anticancer Activity: Comparison of Correlation Weights for Identical SMILES Attributes

    2011

    View DOI
    28 cites
  187. QSPR modeling bioconcentration factor (BCF) by balance of correlations

    2009

    View DOI
    28 cites
  188. Virtual Screening for Aryl Hydrocarbon Receptor Binding Prediction

    2006

    View DOI
    28 cites
  189. Classification of Potential Endocrine Disrupters on the Basis of Molecular Structure Using a Nonlinear Modeling Method

    2004

    View DOI
    28 cites
  190. 28 cites
  191. Intelligent consensus predictions of bioconcentration factor of pharmaceuticals using 2D and fragment-based descriptors

    2022

    View DOI
    27 cites
  192. Review and priority setting for substances that are listed without a specific migration limit in Table 1 of Annex 1 of Regulation 10/2011 on plastic materials and articles intended to come into contact with food

    2020

    View DOI
    27 cites
  193. InChI-based optimal descriptors: QSAR analysis of fullerene[C60]-based HIV-1 PR inhibitors by correlation balance

    2010

    View DOI
    27 cites
  194. EVALUATION OF SOLID PHASE MICROEXTRACTION–GAS CHROMATOGRAPHY IN THE ANALYSIS OF SOME PESTICIDES WITH DIFFERENT MASS SPECTROMETRIC TECHNIQUES: APPLICATION TO ENVIRONMENTAL WATERS AND FOOD SAMPLES

    2002

    View DOI
    27 cites
  195. Involvement of a serine protease in the synthesis of platelet‐activating factor by endothelial cells stimulated by tumor necrosis factor‐α or interleukin‐1α

    1994

    View DOI
    27 cites
  196. Integrating QSAR, Read-Across, and Screening Tools: The VEGAHUB Platform as an Example

    Challenges and Advances in Computational Chemistry and Physics1970book

    View DOI
    27 cites
  197. New approach methodologies to facilitate and improve the hazard assessment of non-genotoxic carcinogens—a PARC project

    2023

    View DOI
    26 cites
  198. Artificial Intelligence Meets Toxicology

    2022

    View DOI
    26 cites
  199. CORAL: model for no observed adverse effect level (NOAEL)

    2015

    View DOI
    26 cites
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  589. Las Vegas Algorithm in the Prediction of Intrinsic Aqueous Solubility of Drug-Like Compounds

    2024

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  590. P22-42: ONTOX Hub Meta Database paving the way for integrated use of New Approach Methodologies in Next Generation Risk Assessment (NGRA)

    2023

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  591. P22-15: The SILIFOOD application: a new tool to support risk assessment of non-evaluated food contact material substances

    2023

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  592. P06-25: Probabilistic Read-Across Assessment of 2-MCPD Leveraging Machine Learning and Qualified Data

    2023

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  593. List of contributors

    2023

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  594. The validation of predictive potential via the system of self-consistent models: the simulation of blood-brain barrier permeation of organic compounds

    2023

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  595. Toward models for bioaccumulation suitable for the pharmaceutical domain

    2023

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  596. Contributors

    2023

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  597. Computational Toxicological Aspects in Drug Design and Discovery, Screening Adverse Effects

    2023

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  598. Binding organophosphate pesticides to acetylcholinesterase: risk assessment using the Monte Carlo method

    2023

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  599. The system of self-consistent models for pesticide toxicity to <i>Daphnia magna</i>

    2023

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  600. Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project

    2023

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  601. P17-05 Development of a tool combining migration modelling and hazard predictions by QSAR models to support the risk assessment of substances migrating from food contact materials

    2022

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  602. Monte Carlo technique to study of the adsorption affinity of azo dyes with applying new statistical criteria of the predictive potential

    2022

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  603. Semi-Quantitative Half-Life Qsar Models for Water, Sediment, and Soil

    2022

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  604. Carcinogenicity prediction using the index of ideality of correlation

    2022

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  605. Monte Carlo technique to study the adsorption affinity of azo dyes by applying new statistical criteria of the predictive potential

    2022

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  606. Quasi-Smiles: Self-Consistent Models for Toxicity of Organic Chemicals to Tadpoles

    2022

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  607. Development and evaluation of QSAR models to screen endocrine disrupting chemicals

    2021

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  608. Dataset related to article "New in silico models to predict in vitro micronucleus induction as marker of genotoxicity"

    2021

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  609. Curated Envirotox database and compound specific Human-Biota TTC from the LIFE+ Vermeer project

    2021

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  610. The Self-organizing Vector of Atom-pairs Proportions: Use to Develop Models for Melting Points

    2021

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  611. The QSAR-search of effective agents towards coronaviruses applying the Monte Carlo method

    2021

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  612. A descriptor-based analysis to highlight the mechanistic rationale of mutagenicity

    2021

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  613. The Monte Carlo method to build up models of the hydrolysis half-lives of organic compounds

    2021

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  614. Datasets of the proposed models for carcinogenicity assessment based on slope factor.

    2020

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  615. Integrating QSAR models predicting acute contact toxicity and mode of action profiling in honey bees (A. mellifera): Data curation using open source databases, performance testing and validation

    2020

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  616. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    2020

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  617. ‘Ideal correlations’ for the predictive toxicity to <i>Tetrahymena pyriformis</i>

    2020

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  618. Modelling quantitative structure activity–activity relationships (QSAARs): auto-pass-pass, a new approach to fill data gaps in environmental risk assessment under the REACH regulation

    2020

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  619. Individual datasets investigating combined toxicity of binary mixtures in bees from laboratory tests

    2019

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  620. Different KNIME workflows for read-across and successive use for weight-of-evidence strategy

    2019

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  621. Genotoxicity induced by metal oxide nanoparticles: a weight of evidence study and effect of particle surface and electronic properties

    2019

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  622. MOESM5 of Methodology of aiQSAR: a group-specific approach to QSAR modelling

    2019

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  623. MOESM1 of Methodology of aiQSAR: a group-specific approach to QSAR modelling

    2019

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  624. MOESM2 of Methodology of aiQSAR: a group-specific approach to QSAR modelling

    2019

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  625. MOESM4 of SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data

    2019

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  626. MOESM1 of SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data

    2019

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  627. MOESM3 of Methodology of aiQSAR: a group-specific approach to QSAR modelling

    2019

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  628. MOESM3 of SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data

    2019

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  629. MOESM4 of Methodology of aiQSAR: a group-specific approach to QSAR modelling

    2019

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  630. Idealized correlations: prediction of solubility of fullerene in organic solvents

    2018

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  631. Development of an in silico model to evaluate in vivo chromosome damaging potential of chemicals

    2018

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  632. Role of in silico tools and text mining in the risk assessment of selected alkaloids

    2018

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  633. Harmonised risk assessment for human health, animal health and ecological risk assessment of combined exposure to multiple chemicals: a food and feed safety perspective

    2018

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  634. MOESM4 of A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications

    2018

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  635. MOESM3 of A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications

    2018

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  636. MOESM2 of A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications

    2018

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  637. Role of in silico tools and text mining in the safety assessment of selected plant coumarins

    2017

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  638. 優先度設定のための(Q)SARツール:印刷紙及び板紙の食品接触材料物質を用いた事例研究【Powered by NICT】

    2017

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  639. QSPR/QSAR Analyses by Means of the CORAL Software

    2016

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  640. A new QSAR model for predicting in vivo micronucleus test results

    2016

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  641. Prioritisation of potentially genotoxic substances migrating from printed paper and board food contact materials using in silico tools

    2016

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  642. 3D human hepatic organoids for testing Fibrosis, Cholestasis and Phospholipidosis

    2016

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  643. Applying (Q)SAR tools in the prioritization of potentially genotoxic substances migrating from printed paper and board food contact materials

    2016

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  644. Identification of potential genotoxicants in food contact materials using in silico tools

    2016

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  645. Improving confidence in (Q)SAR predictions under Canada’s Chemicals Management Plan – a chemical space approach<sup>$</sup>

    2016

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  646. Results of a round-robin exercise on read-across

    2016

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  647. Developing Data Collections for (Q)SAR Modelling of Nanomaterials

    2016

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  648. The challenges associated with developing data collections to support modelling of nanomaterial effects

    2016

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  649. Non-plastic food contact materials: classification of chemicals using predictive models

    2016

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  650. Prediction of long term toxic effects by genome based network models

    2015

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  651. Use of (Q)SAR tools as a first step in a strategy to assign priority to substances migrating from printed paper and board food contact materials based on genotoxic potential

    2015

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  652. <i>In silico</i> exploratory study using structure–activity relationship models and metabolic information for prediction of mutagenicity based on the Ames test and rodent micronucleus assay

    2015

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  653. A new tool to explore reasons of adverse effects, within a read across perspective

    2015

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  654. New software to support read across, based on multiple profilers

    2014

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  655. Building up QSAR model for toxicity of Psychotropic Drugs by the Monte Carlo method. Structural Chemistry

    2014

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  656. ChemInform Abstract: OCWLGI Descriptors: Theory and Praxis

    2013

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  657. In-silico-methoden - Grenzen und möglichkeiten aus unterschiedlichen perspektiven

    2012

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  658. Sharing dose response data and analysis across the SEURAT-1 cluster

    2012

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  659. International workshop on safety assessment of consumer goods coming from recovered materials in a global scale perspective

    2012

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  660. Rigid and flexible topological indices: variety of the representations of the molecular structures.

    2012

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  661. Toxicological and Ecotoxicological Studies for Additives

    2012

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  662. Report on the 1st workshop of the RISKCYCLE coordination action. Hanoi, Vietnam, 4–5 May 2010

    2011

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  663. UNICORE

    2011

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  664. Alternative (non-animal) methods for cosmetics testing: current status and future prospects-2010

    2011

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  665. Applicability and performance evaluation of QSAR models for bioconcentration in fish

    2011

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  666. Disseminating the QSAR models: the ORCHESTRA EC project

    2010

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  667. QSAR Models for Regulatory Purposes: Experiences and Perspectives

    2009

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  668. Computer-aided methodologies to predict endocrine-disrupting potency of chemicals

    2009

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  669. ChemInform Abstract: In silico‐Aided Prediction of Biological Properties of Chemicals: Oestrogen Receptor‐Mediated Effects

    2008

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  670. Open Computing Grid for Molecular Sciences

    2007

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  671. Study of species-specific carcinogenicity of benzene derivatives. 2. Combination of Docking and Local Binding Energy (LBE) analysis

    2007

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  672. Preface

    2007

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  673. Forewords

    2007

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  674. Environmental and Ecological Toxicology: Computational Risk Assessment

    2006

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  675. 3D‐QSAR and Molecular Mechanics Study for the Differences in the Azole Activity Against Yeastlike and Filamentous Fungi and Their Relation to P450DM Inhibition. Part 1. 3‐Substituted‐4(3H)‐quinazolinones.

    2005

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  676. Knowledge Exploration in Life Science Informatics: International Symposium KELSI 2004, Milan, Italy, November 25-26, 2004, Proceedings

    2004

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  677. Predictive Models for Aquatic Toxicity of Aldehydes Designed for Various Model Chemistries.

    2004

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  678. Classification of Potential Endocrine Disrupters on the Basis of Molecular Structure Using a Nonlinear Modeling Method.

    2004

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  679. A Protocol to Select High Quality Datasets of Ecotoxicity Values for Pesticides

    2004

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  680. Computational models for toxicity of allelochemicals

    2004

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  681. Lecture Notes in Artifical Intelligence (Subseries of Lecture Notes in Computer Science): Preface

    2004

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  682. Tuning Neutral and Fuzzy‐Neutral Networks for Toxicity Modeling.

    2003

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  683. Carcinogenicity prediction of aromatic compounds using self-organizing data mining

    2003

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  684. DATABASE MINING WITH ADAPTIVE FUZZY PARTITION: APPLICATION TO THE PREDICTION OF PESTICIDE TOXICITY ON RATS

    2003

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  685. The Importance of Scaling in Data Mining for Toxicity Prediction.

    2002

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  686. Integrating rules and neural nets for carcinogenicity prediction

    2002

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  687. A Comparison of Probabilistic, Neural, and Fuzzy Modeling in Ecotoxicity

    2002

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  688. Results from a Data Mining Approach to Predictive Toxicology: The Case of Pesticide Data

    2002

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  689. ChemInform Abstract: Interpretation of Quantitative Structure—Property and —Activity Relationships.

    2001

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  690. ChemInform Abstract: Predictive Carcinogenicity: A Model for Aromatic Compounds, with Nitrogen‐Containing Substituents, Based on Molecular Descriptors Using an Artificial Neural Network.

    2000

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  691. Prediction of ecotoxicity of pesticides: comparison of multivariate analysis, neural networks, and classifiers.

    2000

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  692. Predictive Toxicology Results Integrating Different AI Paradigms: The Carcinogenicity Case.

    1999

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  693. Analysis of pesticides and related products by chromatography-mass spectrometry

    1996

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  694. ChemInform Abstract: Selective Sulfur Oxygenation in Phosphoroamidate, Thionophosphate, and Thiophosphate Agrochemicals by Perfluoro‐cis‐2,3‐dialkyloxaziridine.

    1995

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  695. Differential metabolic fate of octadecyl-methyl-alycero-3-phosohocholine (ET18-OMe) in tumoral cells, normal cells and isolated and oerfused liver

    1994

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  696. Analysis by fast atom bombardment mass spectrometry of phospholipids from tubuli, glomeruli, and urine of normal rats and rats with acute renal failure

    1992

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  697. Preparation of 4,4′‐diaminodiphenylmethane‐(<sup>2</sup>H<sub>4</sub>) for use as internal standard in the quantification of 4,4′‐diaminodiphenylmethane

    1991

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  698. Identification of microsomal metabolites of spirogermanium.

    1989

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  699. ChemInform Abstract: Reaction of Aldoses with Amino Acids and Proteins. Part 3. Reaction of 2‐Amino‐2‐deoxy‐D‐glucose and Lysine: Isolation and Characterization of 2,5‐Bis(tetrahydroxybutyl)pyrazine.

    1989

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  700. Analysis Of Surface Waters With DifferentExtractive Procedures

    1970

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