Description

Book Synopsis

The AI Trends in Chemical Space for Drug Discovery.- Screening Methods for Drugs Using Chemoinformatics Methods for Beginners.- Data-driven Molecular Structure Generation for Inverse QSPR/QSAR Problem.- Materials Informatics with Limited Data.- Primer on Graph Machine Learning.- Subgraph-based Molecular Graph Generation.- Language Models in Molecular Discovery.- Transformers and Large Language Models for Chemistry and Drug Discovery.- Drug Discovery and Drug Repositioning Using Computational Methods.- Two and Three-dimensional Molecular Representations in Ligand-based Approaches.- Electronic-Structure Informatics for Drug Development.- Data-Driven Chemistry for Developing Organic Synthesis Routes for Functional Chemicals.- Quantum-Chemoinformatics for Design and Discovery of New Molecules and Reactions.- Toxicity Prediction System for Chemical Substances Based on Toxicity Expression Mechanisms - AI-SHIPS.- Data Assimilation to Integrate High-speed Atomic Force Microscopy with Biomolecular Simulations: Characterization of Drug Target Functions.- Potential of High-Spatiotemporal Resolution Live Cell Imaging for Drug Discovery and Development.- Design of Biomaterials Using Informatics.- Monitoring and Controlling in Continuous Manufacturing Process.- Formulation using Hansen Solubility Parameters.

Drug Development Supported by Informatics

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    £142.49

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    RRP £149.99 – you save £7.50 (5%)

    Order before 4pm tomorrow for delivery by Wed 17 Jun 2026.

    A Hardback by Hiroko Satoh

    15 in stock


      View other formats and editions of Drug Development Supported by Informatics by Hiroko Satoh

      Publisher: Springer
      Publication Date: 19/10/2024
      ISBN13: 9789819748273, 978-9819748273
      ISBN10:
      Also in:
      Organic chemistry

      Description

      Book Synopsis

      The AI Trends in Chemical Space for Drug Discovery.- Screening Methods for Drugs Using Chemoinformatics Methods for Beginners.- Data-driven Molecular Structure Generation for Inverse QSPR/QSAR Problem.- Materials Informatics with Limited Data.- Primer on Graph Machine Learning.- Subgraph-based Molecular Graph Generation.- Language Models in Molecular Discovery.- Transformers and Large Language Models for Chemistry and Drug Discovery.- Drug Discovery and Drug Repositioning Using Computational Methods.- Two and Three-dimensional Molecular Representations in Ligand-based Approaches.- Electronic-Structure Informatics for Drug Development.- Data-Driven Chemistry for Developing Organic Synthesis Routes for Functional Chemicals.- Quantum-Chemoinformatics for Design and Discovery of New Molecules and Reactions.- Toxicity Prediction System for Chemical Substances Based on Toxicity Expression Mechanisms - AI-SHIPS.- Data Assimilation to Integrate High-speed Atomic Force Microscopy with Biomolecular Simulations: Characterization of Drug Target Functions.- Potential of High-Spatiotemporal Resolution Live Cell Imaging for Drug Discovery and Development.- Design of Biomaterials Using Informatics.- Monitoring and Controlling in Continuous Manufacturing Process.- Formulation using Hansen Solubility Parameters.

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