Big data in predictive toxicology / edited by Daniel Neagu and Andrea-Nicole Richarz

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Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Issues in toxicology ; 41Publisher: Cambridge : Royal Society of Chemistry, [2020]Copyright date: © 2020Description: 1 Online-Ressource (xx, 393 Seiten) : Illustrationen, DiagrammeISBN:

9781782623656

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Additional physical formats: 9781782622987 | Erscheint auch als: Big data in predictive toxicology. Druck-Ausgabe. Cambridge : Royal Society of Chemistry, 2020. xx, 393 SeitenDDC classification:

542/.85

LOC classification:

QD39.3.E46

DOI: DOI: 10.1039/9781782623656Online resources:

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Summary: Big Data in Predictive Toxicology - Challenges, Opportunities and Perspectives; Biological Data in the Light of Toxicological Risk Assessment; Chemoinformatics Representation of Chemical Structures : A Milestone for Successful Big Data Modelling in Predictive Toxicology; Organisation of Toxicological Data in Databases; Making Big Data Available: Integrating Technologies for Toxicology Applications; Storing and Using Qualitative and Quantitative Structure:Activity Relationships in the Era of Toxicological and Chemical Data Expansion; Toxicogenomics and Toxicoinformatics: Supporting Systems Biology in the Big Data Era; Profiling the Tox21 Chemical Library for Environmental Hazards: Applications in Prioritisation, Predictive Modelling, and Mechanism of Toxicity Characterisation; Big Data Integration and Inference; Chemometrical Analysis of Proteomics Data; Big Data and Biokinetics; Role of Toxicological Big Data to Support Read-Across for the Assessment of ChemicalsPPN: PPN: 1680871374Package identifier: Produktsigel: ZDB-1-RSEK

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