Computational Toxicology: Volume II by Brad ReisfeldComputational Toxicology: Volume II by Brad Reisfeld

Computational Toxicology: Volume II

EditorBrad Reisfeld, Arthur N. Mayeno

Hardcover | October 21, 2012

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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 applied and basic science, from streamlining drug efficacy and safety testing, to increasing the efficiency and effectiveness of risk assessment for environmental chemicals. Computational Toxicology was conceived to provide both experienced and new biomedical and quantitative scientists with essential background, context, examples, useful tips, and an overview of current developments in the field. This two-volume set serves as a resource to help introduce and guide readers in the development and practice of these tools to solve problems and perform analyses in this area.Divided into six sections, Volume II covers a wide array of methodologies and topics. The volume begins by exploring the critical area of predicting toxicological and pharmacological endpoints, as well as approaches used in the analysis of gene, signaling, regulatory, and metabolic networks. The next section focuses on diagnostic and prognostic molecular indicators (biomarkers), followed by the application of modeling in the context of government regulatory agencies.  Systems toxicology approaches are also introduced. The volume closes with primers and background on some of the key mathematical and statistical methods covered earlier, as well as a list of other resources. Written in a format consistent with the successful Methods in Molecular BiologyT series where possible, chapters include introductions to their respective topics, lists of the necessary materials and software tools used, methods, and notes on troubleshooting and avoiding known pitfalls.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.
Title:Computational Toxicology: Volume IIFormat:HardcoverDimensions:659 pagesPublished:October 21, 2012Publisher:Humana PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:1627030581

ISBN - 13:9781627030588

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Table of Contents

Part 1. Toxicological/Pharmacological Endpoint Prediction 1. Methods for Building QSARs            James Devillers 2. Accessing and Using Chemical Databases            Nikolai Nikolov, Todor Pavlov, Jay R. Niemelä, and Ovanes Mekenyan 3. From QSAR to QSIIR: Searching for Enhanced Computational Toxicology Models            Hao Zhu 4. Mutagenicity, Carcinogenicity and Other Endpoints            Romualdo Benigni, Chiara Laura Battistelli, Cecilia Bossa, Mauro Colafranceschi, and Olga Tcheremenskaia 5. Classification Models for Safe Drug Molecules            A.K. Madan, Sanjay Bajaj, and Harish Dureja 6. QSAR and Metabolic Assessment Tools in the Assessment of Genotoxicity            Andrew P. Worth, Silvia Lapenna, and Rositsa Serafimova Part II. Biological Network Modeling 7. Gene Expression Networks            Reuben Thomas and Christopher J. Portier 8. Construction of Cell Type-Specific Logic Models of Signaling Networks Using CellNetOptimizer            Melody K. Morris, Ioannis Melas, and Julio Saez-Rodriguez 9. Regulatory Networks            Gilles Bernot, Jean-Paul Comet, and Christine Risso- de Faverney 10. Computational Reconstruction of Metabolic Networks from KEGG            Tingting Zhou Part III. Biomarkers  11. Biomarkers            Harmony Larson, Elena Chan, Sucha Sudarsanam, and Dale E. Johnson 12. Biomarkers: Environmental Public Health Indicators            Andrey I. Egorov, Dafina Dalbokova, and Michal Kryzanowski Part IV. Modeling for Regulatory Purposes (Risk and Safety Assessment) 13. Modeling for Regulatory Purposes (Risk and Safety Assessment)            Hisham El-Masri 14. Developmental Toxicity Prediction            Raghuraman Venkatapathy and Nina Ching Y. Wang 15. Predictive Computational Toxicology to Support Drug Safety Assessment            Luis G. Valerio, Jr.  Part V. Integrated Modeling/Systems Toxicology Approaches 16. Developing a Practical Toxicogenomics Data Analysis System Utilizing Open-Source Software            Takehiro Hirai and Naoki Kiyosawa 17. Systems Toxicology from Genes to Organs             John Jack, John Wambaugh, and Imran Shah 18. Agent Based Models of Cellular Systems            Nicola Cannata, Flavio Corradini, Emanuela Merelli, and Luca Tesei Part VI. Mathematical and Statistical Background 19. Linear Algebra            Kenneth Kuttler 20. Ordinary Differential Equations            Jirí Lebl 21. On the Development and Validation of QSAR Models            Paola Gramatica 22. Principal Components Analysis            Detlef Groth, Stefanie Hartmann, Sebastian Klie, and Joachim Selbig 23. Partial Least Square Methods: Partial Least Squares Correlation and Partial Least Square Regression            Hervé Abdi and Lynne J. Williams 24. Maximum Likelihood            Shuying Yang and Daniela De Angelis 25. Bayesian Inference             Frédéric Y. Bois