Atjaunināt sīkdatņu piekrišanu

Computational Toxicology: Methods and Protocols Second Edition 2025 [Hardback]

  • Formāts: Hardback, 445 pages, height x width: 254x178 mm, 3 Illustrations, black and white; XIV, 445 p. 3 illus., 1 Hardback
  • Sērija : Methods in Molecular Biology 2834
  • Izdošanas datums: 24-Sep-2024
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 107164002X
  • ISBN-13: 9781071640029
  • Hardback
  • Cena: 154,01 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Standarta cena: 181,19 €
  • Ietaupiet 15%
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
  • Formāts: Hardback, 445 pages, height x width: 254x178 mm, 3 Illustrations, black and white; XIV, 445 p. 3 illus., 1 Hardback
  • Sērija : Methods in Molecular Biology 2834
  • Izdošanas datums: 24-Sep-2024
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 107164002X
  • ISBN-13: 9781071640029
This second eidtion explores new and updated techniques used to understand solid target-specific models in computational toxicology.  Chapters are divided into four sections, detailing molecular descriptors, QSAR and read-across, molecular and data modeling techniques, computational toxicology in drug discovery, molecular fingerprints, AI techniques, and safe drug design. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.





Authoritative and cutting-edge, Computational Toxicology: Methods and Protocols, Second Editon aims to ensure successful results in the further study of this vital field.
QSAR: Using the Past to Study the Present.- Molecular similarity in
predictive toxicology with a focus on the q-RASAR technique.- Weight of
Evidence: criteria and applications.- Integration of QSAR and NAM in the Read
Across process for an effective and relevant toxicological assessment.-
Automated workflows for data curation and machine learning to develop
Quantitative Structure-Activity Relationships.- Applicability Domain for
Trustable Predictions.- The potential of molecular docking for predictive
toxicology.- Computational toxicology methods in chemical library design and
high-throughput screening hit validation.- Toxicity potential of
nutraceuticals.- Development, use and validation of (Q)SARs for predicting
genotoxicity and carcinogenicity: experiences from Italian National Institute
of Health activities .- Adverse outcome pathways mechanistically describing
hepatotoxicity.- Machine learning in early prediction of metabolism of
drugs.- In vitro cell-based MTT and Crystal Violet assays for drug toxicity
screening.- Recent advances in nanodrug delivery systems production,
efficacy, safety and toxicity.- Investigating the benefit-risk profile of
drugs: from spontaneous reporting systems to real word data for
pharmacovigilance.- MolPredictX a Pioneer Mobile App Version for Online
Biological Activity Predictions by Machine Learning Models.- TIRESIA and
TISBE, explainable artificial intelligence based web platforms for the
transparent assessment of the developmental toxicity of chemicals and drugs.-
PFAS-Biomolecule Interactions:  Case Study Using Asclepios Nodes and
automated Workflows in KNIME for Drug Discovery and Toxicology.