Cantitate/Preț
Produs
Total produse
Vezi coșul
Predictive Toxicology de Christoph Helma

Predictive Toxicology

Editat de Christoph Helma
en Limba Engleză Hardback – 17 mar 2005
A comprehensive overview of techniques and systems currently utilized in predictive toxicology, this reference presents an in-depth survey of strategies to characterize chemical structures and biological systems—covering prediction methods and algorithms, sources of high-quality toxicity data, the most important commercial and noncommercial predictive toxicology programs, and advanced technologies in computational chemistry and biology, statistics, and data mining.
Citește tot Restrânge

Preț: 139696 lei

Preț vechi: 205526 lei
-32% Nou

Puncte Express: 2095
Preț estimativ în valută:
24720€ • 28987$ • 21709£

Comandă specială

Livrare economică 09-23 ianuarie 26

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Doresc să fiu notificat când acest titlu va fi disponibil:
Trimite
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9780824723972
ISBN-10: 082472397X
Pagini: 520
Ilustrații: 74 b/w images, 36 color images, 27 tables and 113 equations
Dimensiuni: 152 x 229 x 29 mm
Greutate: 0.91 kg
Ediția:New.
Editura: CRC Press
Colecția CRC Press
Locul publicării:Boca Raton, United States

Public țintă

Professional

Cuprins

A Brief Introduction to Predictive Toxicology. Description and Representation of Chemicals. Computational Biology and Toxicogenomics. Toxicological Information for Use in Predictive Modeling: Quality, Sources, and Databases. The Use of Expert Systems for Toxicology Risk Prediction. Regression- and Projection-Based Approaches in Predictive Toxicology. Machine Learning and Data Mining. Neural Networks and Kernel Machines for Vector and Structured Data. Applications of Substructure-Based SAR in Toxicology. OncoLogic: A Mechanism-Based Expert System for Predicting the Carcinogenic Potential of Chemicals. META: An Expert System for the Prediction of Metabolic Transformations. MC4PC—An Artificial Intelligence Approach to the Discovery of Quantitative Structure-Toxic Activity Relationships. PASS: Prediction of Biological Activity Spectra for Substances. Lazar: Lazy Structure-Activity Relationships for Toxicity Prediction. Index.

Recenzii

“… This reference book presents an in-depth survey of strategies to characterize chemical structures and biological systems, covering prediction methods and algorithms, sources of high-quality toxicity data, the most important commercial and non-commercial predictive toxicology programs, and advanced technologies in computational chemistry and biology, statistics, and data mining. … Valuable to readers in a variety of disciplines, such as toxicologists, pharmacologists, computer scientists, statisticians, and researchers in environmental toxicology and drug design, this guide provides demonstrations of various algorithms and their capabilities to select, calculate, and represent the features and properties of chemical structures, demonstrations that og beyond the classical structure-activity relationships.”
— J Albaigés, Editor in Chief, Department of Environment Chemistry CID-CSIC, Barcelona, Spain, in International Journal Of Environmental Analytical Chemistry, Vol. 86, 2006
“…provides in-depth reviews of subjects widely considered by workers in this developing field.”
—Toxicology Letters
“…After using the book, practitioners are likely to have gained a stronger sense of the methodologies behind the techniques….a valuable resource for a field that is quickly developing in practicality.”
—Doody’s Reviews

Notă biografică

Christoph Helma, University of Freiburg, Germany

Descriere

A comprehensive overview of techniques and systems currently utilized in predictive toxicology, this reference presents an in-depth survey of strategies, algorithms, and prediction methods to select, calculate, and represent the features and properties of chemical structures in biological systems. It provides sources of high-quality toxicity data, the most important commercial and noncommercial predictive toxicology programs, and advanced technologies in computational chemistry, biology, statistics, and data mining. Predictive Toxicology explores applications that go beyond classical structure–activity relationships and discusses programs such as OncoLogic, META, MC4PC, PASS, and lazar.