XI, 648 p. 153 illus., 62 illus. in color., digital.
SERIES
Series Title
(Methods in Molecular Biology, Methods and Protocols,1064-3745
Volume Designation
; 930)
NOTES PERTAINING TO PUBLICATION, DISTRIBUTION, ETC.
Text of Note
Electronic
CONTENTS NOTE
Text of Note
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 a??best practicesa?? 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?aan overview of molecular dynamics.?a 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 Biologya?o 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.
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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.
SERIES
Title
Methods in Molecular Biology, Methods and Protocols,1064-3745