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Advances in QSAR Modeling

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Cover of 'Advances in QSAR Modeling'

Table of Contents

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    Book Overview
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    Chapter 1 Towards the Revival of Interpretable QSAR Models
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    Chapter 2 The Use of Topological Indices in QSAR and QSPR Modeling
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    Chapter 3 Which Performance Parameters Are Best Suited to Assess the Predictive Ability of Models?
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    Chapter 4 Structural, Physicochemical and Stereochemical Interpretation of QSAR Models Based on Simplex Representation of Molecular Structure
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    Chapter 5 The Maximum Common Substructure (MCS) Search as a New Tool for SAR and QSAR
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    Chapter 6 Generative Topographic Mapping Approach to Chemical Space Analysis
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    Chapter 7 On Applications of QSARs in Food and Agricultural Sciences: History and Critical Review of Recent Developments
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    Chapter 8 Quantitative Structure-Epigenetic Activity Relationships
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    Chapter 9 QSAR/QSPR Modeling in the Design of Drug Candidates with Balanced Pharmacodynamic and Pharmacokinetic Properties
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    Chapter 10 Strategy for Identification of Nanomaterials’ Critical Properties Linked to Biological Impacts: Interlinking of Experimental and Computational Approaches
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    Chapter 11 In Silico Approaches for the Prediction of In Vivo Biotransformation Rates
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    Chapter 12 Development of Monte Carlo Approaches in Support of Environmental Research
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    Chapter 13 Environmental Toxicity of Pesticides, and Its Modeling by QSAR Approaches
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    Chapter 14 Counter-Propagation Artificial Neural Network Models for Prediction of Carcinogenicity of Non-congeneric Chemicals for Regulatory Uses
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    Chapter 15 Big Data in Structure-Property Studies—From Definitions to Models
Attention for Chapter 5: The Maximum Common Substructure (MCS) Search as a New Tool for SAR and QSAR
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Chapter title
The Maximum Common Substructure (MCS) Search as a New Tool for SAR and QSAR
Chapter number 5
Book title
Advances in QSAR Modeling
Published by
Springer International Publishing, May 2017
DOI 10.1007/978-3-319-56850-8_5
Book ISBNs
978-3-31-956849-2, 978-3-31-956850-8
Authors

Azadi Golbamaki, Alessio Mauro Franchi, Giuseppina Gini

Editors

Kunal Roy

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 33%
Student > Bachelor 1 17%
Other 1 17%
Student > Master 1 17%
Researcher 1 17%
Other 0 0%
Readers by discipline Count As %
Environmental Science 1 17%
Biochemistry, Genetics and Molecular Biology 1 17%
Chemistry 1 17%
Engineering 1 17%
Design 1 17%
Other 0 0%
Unknown 1 17%