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computational-toxicology-2013

computational-toxicology-2013

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Chapter 1 Methods for Building QSARs

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3 Molecular Descriptors

3 2 2D Molecular Descriptors

6 Model Performance Estimation

7 Interpreting the Models

8 Concluding Remarks

4 2 OASIS Centralized Database

Chapter 2 Accessing and Using Chemical Databases

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4 3 The Danish QSAR Database Online

5 Relational Databases

6 Examples of Chemical Database Resources Online

2 Availability of Large Compound Collections for In Vivo and In Vitro Toxicity Evaluation

Chapter 3 From QSAR to QSIIR Searching for Enhanced Computational Toxicology Models

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3 QSAR and Current Challenge of Computational Toxicology

4 Quantitative Structure In Vitro–In Vivo Relationship

5 Case Studies 5 1 Using “Hybrid” Descriptors for QSIIR Modeling of Rodent Carcinogenicity

Chapter 4 Mutagenicity, Carcinogenicity, and Other End points

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2 Structure–Activity Relationships and the Prediction of Toxicological End points

3 Sar Based Expert Systems

3 2 Toxtree

3 3 OECD QSAR Application Toolbox

4 Support Tools for Structure–Activity Relationships Work

4 2 Databases on Chemical Toxicological

Chapter 5 Classification Models for Safe Drug Molecules

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2 Materials and Methods

2 2 Pattern Recognition Pattern recognition is a term

2 7 Ensemble method utilizes a combination of techniques for con

2 8 Bayes Classifier 2 9 Moving Average Analysis

3 Conclusion

QSAR and Metabolic Assessment Tools

Chapter 6 QSAR and Metabolic Assessment Tools

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2 Materials 2 1 CAESAR 2 2 Derek for

2 3 HazardExpert 2 4 Lazar 2 5 Meteor

2 6 OECD QSAR Toolbox The OECD QSAR Toolbox is a stand alone software application

2 9 ToxBoxes 2 10 Toxtree

3 Methods 3 1 Stepwise

4 Case Studies on the Application of Computational Methods

4 2 5 General Conclusions for 2 Aminoacetophenone

5 Concluding Remarks

Chapter 7 Gene Expression Networks

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Abstract

2 Materials and Methods

2 2 Accessing Publicly Available Gene

2 3 Identifying Toxicologically Relevant Gene Expression Networks 2 3 1 Gene Set or

2 4 Reverse Engineering Gene Expression Networks

3 Examples 3 1 Immune Response Pathways in the Blood Perturbed at Low

Disclaimer

3 Methods 3 1 Logic Modeling in CellNOpt

Chapter 8 Construction of Cell Type Specific Logic Models of Signaling Networks Using CellNOpt

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3 2 Experimental Design of Datasets

3 3 Loading the Prior Knowledge Network and Data into CellNOpt

3 4 Training a Logic Model with CellNOpt

3 5 Model Analysis

4 Examples 4 1 Simple Toy Example

4 2 Application to Data From the Hepatocyte Cell Line HepG2

Chapter 9 Regulatory Networks

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2 Example Detoxification

3 Method Thomas’

3 2 Structure Regulatory Graphs

3 3 Dynamics State Graphs

4 An Example of Possible

5 Materials Model Checking

5 2 CTL to Encode Biological Properties

5 3 Computer Aided Elaboration of Formal Model

3 3 Local Database Design

Chapter 10 Computational Reconstruction of Metabolic Networks from KEGG

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4 Applications of the Reconstructed

1 1 Biomarkers of Adverse Drug Reaction

Chapter 11 Biomarkers

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1 2 Pharmacogenomic Biomarkers for Potential

1 3 Computational Approaches for Safety Biomarker

2 Materials 2 1 Animal Study

3 2 Inferring Human Endpoints from Animal Data

4 Examples

4 1 More Complex Problem

Materials and Methods 2 1 Matrices Used for Biomonitoring 2 1 1 Blood

Chapter 12

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2 2 Examples of Biomonitoring Programs 2 3 Interpretation

2 3 Interpretation

3 Examples 3 1 Environment

3 2 ENHIS Indicator “Persistent Organic Pollutants in Human Milk”

3 2 2 Dioxin Levels

3 2 3 Levels of Polybrominated Diphenyl Ethers and Other POPs in Human Milk

4 Notes

Chapter 13

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Abstract

1 DoseResponse Relationships

1 1 Point of Departure Estimates

1 2 Modeling Dose–Response Data

2 Balancing and Judging Uncertainty

2 Materials 2 1 Types of QSAR Models

Chapter 14

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2 2 Prebuilt Commercial Noncommercial

2 3 Developing Q SAR Models to Predict Developmental

2 3 1 Software Suites for Developing QSARs

2 3 2 Unbundled Software for Developing QSARs

3 Methods 3 1 QSAR Analysis

3 2 Independent Variables

3 3 Datasets

3 4 Statistical Analysis

3 5 Domain of Applicability

3 6 Performance Evaluation of a QSAR Model

Chapter 15

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2 Materials andMethods

Chapter 16

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2 Open Source Software

3 Methods 3 1 Gene Expression Data Sets

3 2 Preparation

3 3 Development and Implementation of Automated TGx Data Processing System

4 Practical Examples

4 2 Example 2 Application of D Score for Compound Screening

Chapter 17

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2 Systems Toxicology Challenges

2 1 Defining the “System”

2 2 Computational Systems for Toxicology

2 3 Probing Systems Multiresolution Data

3 Methods for Dynamic Systems Modeling

3 2 Cell Based Models

3 3 Molecular Systems Models

3 6 Multiscale Simulation

4 Methods for System Reconstruction

5 Agent Based Models of Tissues

5 2 ABM Construction

5 3 Cellular and Microvascular

6 Conclusion

Chapter 18

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1 2 Agent Based Modeling

1 3 Review of ABM of Cellular Systems

Chapter 19

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Abstract

2 The Inner Product and Dot Product

5 Matrix Multiplication

6 Systems of Linear Equations and Matrices

7 Row Operations When one deals with matrices there are operations called row operations

12 Permuting Rows or Columns

8 Properties ofMatrix

13 A Symmetric Definition

14 Properties of Determinants

15 Cofactor Expansions

16 Formula for the Inverse

18 UpperTriangular Matrices

20 Schur’s Theorem Consider the following system of equations

21 Symmetric and HermitianMatrices

22 The Square Root

23 An Application to Statistics

24 The Singular Value

25 Approximation intheFrobenius

26 Finding the Singular Value Decomposition From the construction

27 LeastSquares andSingularValue

28 Linear Regressions An important applicationof least squares is to theproblemof finding a str

29 The Moore Penrose Inverse

Ordinary Differential Equations

Chapter 20

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1 2 Systemsof DifferentialEquations

1 3 Analytical Versus Numerical Solutions 1 4 Further Reading

2 Analytical Methods 2 1 First Order Equations 2 1 1 The Exponential

2 2 Systems of ODEs 2 2 1 Linear First Order

3 Numerical Methods 3 1 Euler’s Method

3 2 Fourth Order Runge–Kutta

3 3 Systems and Higher Order Equations The

On the Development and Validation of QSAR Models Abstract

Chapter 21

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2 Important Concepts 2 1 Input

2 2 Molecular Descriptors The Independent

2 3 Data Exploration by Principal

2 4 Statistical Methods Regression

2 4 1 Variable Selection

2 5 Validation of QSAR Models OECD Principle 4

2 6 QSAR models

2 7 Other Statistical Modelling Methods

2 8 Applicability Domain

Examples

Principal Components Analysis Abstract

Chapter 21

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2 Important Concepts 2 1 Data Normalization

2 2 Principal Components Analysis We next

3 Biological Examples 3 1 Sequence Data Analysis

3 2 Metabolite Data Analysis In this example we employ

3 4 Statistical Analysis

5 Availability of R Code

3 The Main Tool The Singular Value

Chapter 23

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4 Partial Least Squares Correlation 4 1 Correlation Between

4 1 Correlation Between

4 4 Significance 4 4 1 Permutation Test for Omnibus Tests and

4 5 PLSC Example We will illustrate

5 PartialLeast SquareRegression Partial

5 1 Iterative Computation of the Latent Variables

5 2 What Does PLSR Optimize

5 4 PLSRExample Wewillusethesameexampleas

Chapter 24

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Maximum Likelihood Abstract

2 Important Concepts 2 1 Likelihood

2 2 Maximum LikelihoodEstimation

2 3 Properties of MLE 2 3 1 Asymptotically MLE

2 4 Confidence Interval from MLE

3 Examples 3 1 Maximum LikelihoodEstimation ofExponential Distribution

3 3 LinearRegression Assume

3 4 DoseResponse Model

2 Important Concepts 2 1 Random Variables

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Chapter 25

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2 3 Multilevel Hierarchical Models

2 4 Mixture Models

2 6 Conditioning on the Data to Update

2 7 Quantifying Prior Knowledge

2 8 Getting at the Posterior Analytical solutions

2 9 Checking the Results

2 10 Inference and Decision

3 An Example of Application

3 2 Statistical Models

3 3 Embedded PBPK Model

3 4 Choosing the Priors

3 5 Computing the Posterior

3 6 Checking the Models

3 7 Inference on Model Structure

3 8 Making Predictions

3 9 Conclusion of the Example