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Methods in Molecular Biology #930: Computational Toxicology: Volume II

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Methods in Molecular Biology #930: Computational Toxicology: Volume II Cover

 

Synopses & Reviews

Publisher Comments:

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.

Synopsis:

This resource features essential background, context, examples, useful tips, and an overview of current developments in the field. It includes cutting-edge methods and protocols as well as implementation advice from the experts.

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 Jiří 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

Product Details

ISBN:
9781627030588
Author:
Reisfeld, Brad
Publisher:
Humana Press
Author:
Mayeno, Arthur N.
Subject:
Pharmacology
Subject:
QSAR
Subject:
biological network modeling
Subject:
biomarkers
Subject:
gene expression networks
Subject:
Regulatory networks
Subject:
Pharmacology/Toxicology
Subject:
Computer Appl. in Life Sciences
Subject:
Health and Medicine-Pharmacology
Copyright:
Edition Description:
2012
Series:
Methods in Molecular Biology
Series Volume:
Volume II
Publication Date:
20120831
Binding:
HARDCOVER
Language:
English
Pages:
659

Related Subjects

Computers and Internet » Computers Reference » Computerized Home and Entertainment
Health and Self-Help » Health and Medicine » Medical Specialties
Health and Self-Help » Health and Medicine » Pharmacology
Science and Mathematics » Biology » Cytology and Cell Biology
Science and Mathematics » Biology » General

Methods in Molecular Biology #930: Computational Toxicology: Volume II New Hardcover
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Product details 659 pages Humana Press - English 9781627030588 Reviews:
"Synopsis" by , This resource features essential background, context, examples, useful tips, and an overview of current developments in the field. It includes cutting-edge methods and protocols as well as implementation advice from the experts.
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