Computational Toxicology : Volume II / edited by Brad Reisfeld, Arthur N. Mayeno.

Format:

Book

Contributor:

Reisfeld, Brad, editor.

Mayeno, Arthur N., 1961- editor.

SpringerLink (Online service)

Series:

Methods in Molecular Biology, Methods and Protocols, 1064-3745 ; 930.

Springer Protocols (Springer-12345)

Methods in Molecular Biology, Methods and Protocols, 1064-3745 ; 930

Language:

English

Subjects (All):

Medicine.

Pharmacology.

Bioinformatics.

Computational biology.

Biomedicine.

Pharmacology/Toxicology.

Computer Appl. in Life Sciences.

Local Subjects:

Biomedicine.

Pharmacology/Toxicology.

Computer Appl. in Life Sciences.

Physical Description:

1 online resource (XI, 648 pages) : 153 illustrations, 62 illustrations in color.

Contained In:

Springer eBooks

Place of Publication:

Totowa, NJ : Humana Press : Imprint: Humana Press, 2013.

System Details:

text file PDF

Summary:

Rapid advances in computer science, biology, chemistry, and other disciplines are enabling powerful new computational tools and models for toxicology and pharmacology. These computational tools hold tremendous promise for advancing science, from streamlining drug efficacy and safety testing, to increasing the efficiency and effectiveness of risk assessment for environmental chemicals. Computational Toxicology provides biomedical and quantitative scientists with essential background, context, examples, useful tips, and an overview of current developments in the field. Divided into four sections, Volume I covers a wide array of methodologies and topics. Opening with an introduction to the field of computational toxicology and its current and potential applications, the volume continues with 'best practices' in mathematical and computational modeling, followed by chemoinformatics and the use of computational techniques and databases to predict chemical properties and toxicity, as well as an overview of molecular dynamics. The final section is a compilation of the key elements and main approaches used in pharmacokinetic and pharmacodynamic modeling, including the modeling of absorption, compartment and non-compartmental modeling, physiologically based pharmacokinetic modeling, interspecies extrapolation, and population effects. Written in the successful Methods in Molecular Biology™ series format where possible, chapters include introductions to their respective topics, lists of the materials and software tools used, methods, and notes on troubleshooting. Authoritative and easily accessible, Computational Toxicology will allow motivated readers to participate in this exciting field and undertake a diversity of realistic problems of interest.

Contents:

Methods for Building QSARs

Accessing and Using Chemical Databases

From QSAR to QSIIR: Searching for Enhanced Computational Toxicology Models

Mutagenicity, Carcinogenicity and Other Endpoints

Classification Models for Safe Drug Molecules

QSAR and Metabolic Assessment Tools in the Assessment of Genotoxicity

Gene Expression Networks

Construction of Cell Type-Specific Logic Models of Signaling Networks Using CellNetOptimizer

Regulatory Networks

Computational Reconstruction of Metabolic Networks from KEGG

Biomarkers

Biomarkers: Environmental Public Health Indicators

Modeling for Regulatory Purposes (Risk and Safety Assessment)

Developmental Toxicity Prediction

Predictive Computational Toxicology to Support Drug Safety Assessment

Developing a Practical Toxicogenomics Data Analysis System Utilizing Open-Source Software

Systems Toxicology from Genes to Organs

Agent Based Models of Cellular Systems

Linear Algebra

Ordinary Differential Equations

On the Development and Validation of QSAR Models

Principal Components Analysis

Partial Least Square Methods: Partial Least Squares Correlation and Partial Least Square Regression

Maximum Likelihood

Bayesian Inference.

Other Format:

Printed edition:

ISBN:

9781627030595

Access Restriction:

Restricted for use by site license.