1st Edition

Expert Systems in Chemistry Research

By Markus C. Hemmer Copyright 2008
    416 Pages 91 B/W Illustrations
    by CRC Press

    Expert systems allow scientists to access, manage, and apply data and specialized knowledge from various disciplines to their own research. Expert Systems in Chemistry Research explains the general scientific basis and computational principles behind expert systems and demonstrates how they can improve the efficiency of scientific workflows and support decision-making processes.

    Focused initially on clarifying the fundamental concepts, limits, and drawbacks of using computer software to approach human decision making, the author also underscores the importance of putting theory into practice. The book highlights current capabilities for planning and monitoring experiments, scientific data management and interpretation, chemical characterization, problem solving, and methods for encoding chemical data. It also examines the challenges as well as requirements, strategies, and considerations for implementing expert systems effectively in an existing laboratory software environment.

    Expert Systems in Chemistry Research covers various artificial intelligence technologies used to support expert systems, including nonlinear statistics, wavelet transforms, artificial neural networks, genetic algorithms, and fuzzy logic. This definitive text provides researchers, scientists, and engineers with a cornerstone resource for developing new applications in chemoinformatics, systems design, and other emerging fields.

    INTRODUCTION
    What We Are Talking About
    The Concise Summary
    Some Initial Thoughts
    BASIC CONCEPTS OF EXPERT SYSTEMS
    What Are Expert Systems?
    The Conceptual Design of an Expert System
    Knowledge and Knowledge Representation
    Reasoning
    The Fuzzy World
    Gathering Knowledge — Knowledge Engineering
    DEVELOPMENT TOOLS FOR EXPERT SYSTEMS
    The Technical Design of Expert Systems
    Imperative versus Declarative Programming
    List Processing (LISP)
    Programming Logic — PROLOG
    NASA’s Alternative — C Language Integrated Production System (CLIPS)
    Java-Based Expert Systems — JESS
    Rule Engines — JBoss Rules
    Languages for Knowledge Representation
    Advanced Development Tools
    DEALING WITH CHEMICAL INFORMATION
    Structure Representation
    Searching for Chemical Structures
    Describing Molecules
    Descriptive Statistics
    Capturing Relationships — Principal Components
    Transforming Descriptors
    Learning from Nature — Artificial Neural Networks
    Genetic Algorithms (GAs)
    APPLYING MOLECULAR DESCRIPTORS
    Radial Distribution Functions
    Making Things Comparable — Postprocessing of RDF Descriptors
    Adding Properties — Property-Weighted Functions
    Describing Patterns
    From the View of an Atom — Local and Restricted RDF Descriptors
    Straight or Detour — Distance Function Types
    Constitution and Conformation
    Constitution and Molecular Descriptors
    Constitution and Local Descriptors
    Constitution and Conformation in Statistical Evaluations
    Extending the Dimension — Multidimensional Function Types
    Emphasizing the Essential — Wavelet Transforms
    A Tool for Generation and Evaluation of RDF Descriptors — ARC
    Synopsis
    EXPERT SYSTEMS IN FUNDAMENTAL CHEMISTRY
    How It Began — The DENDRAL Project
    A Forerunner in Medical Diagnostics
    Early Approaches in Spectroscopy
    Creating Missing Information — Infrared Spectrum Simulation
    From the Spectrum to the Structure — Structure Prediction
    From Structures to Properties
    Dealing with Localized Information — Nuclear Magnetic Resonance Spectroscopy
    Applications in Analytical Chemistry
    Simulating Biology
    Supporting Organic Synthesis
    EXPERT SYSTEMS IN OTHER AREAS OF CHEMISTRY
    Bioinformatics
    Environmental Chemistry
    Geochemistry and Exploration
    Engineering
    EXPERT SYSTEMS IN THE LABORATORY ENVIRONMENT
    Regulations
    The Software Development Process
    Knowledge Management
    Data Warehousing
    The Basis — Scientific Data Management Systems
    Managing Samples — Laboratory Information Management Systems (LIMS)
    Tracking Workflows — Workflow Management Systems
    Scientific Documentation — Electronic Laboratory Notebooks (ELNs)
    Scientific Workspaces
    Interoperability and Interfacing
    Access Rights and Administration
    Electronic Signatures, Audit Trails, and IP Protection
    Approaches for Search and Reuse of Data and Information
    A Bioinformatics LIMS Approach
    Handling Process Deviations
    Rule-Based Verification of User Input
    OUTLOOK
    Attempting a Definition
    Some Critical Considerations
    Looking Forward
    INDEX
    *Each chapter contains an Introduction, References, and a Concise Summary of the most important concepts

    Biography

    Markus C. Hemmer