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Computational Discovery of Scientific Knowledge

Introduction, Techniques, and Applications in Environmental and Life Sciences

  • Book
  • © 2007

Overview

Editors:
  1. Sašo Džeroski
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    You can also search for this editor in PubMed   Google Scholar

  2. Ljupčo Todorovski
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4660)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Table of contents (15 chapters)

  1. Front Matter

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  2. Computational Discovery of Scientific Knowledge

    1. Computational Discovery of Scientific Knowledge

      • Sašo Džeroski, Pat Langley, Ljupčo Todorovski
      Pages 1-14

  3. I Equation Discovery and Dynamic Systems Identification

    1. Front Matter

      Pages 15-15
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    2. Communicable Knowledge in Automated System Identification

      • Reinhard Stolle, Elizabeth Bradley
      Pages 17-43

    3. Incorporating Engineering Formalisms into Automated Model Builders

      • Matthew Easley, Elizabeth Bradley
      Pages 44-68

    4. Integrating Domain Knowledge in Equation Discovery

      • Ljupčo Todorovski, Sašo Džeroski
      Pages 69-97

    5. Communicability Criteria of Law Equations Discovery

      • Takashi Washio, Hiroshi Motoda
      Pages 98-119

    6. Quantitative Revision of Scientific Models

      • Kazumi Saito, Pat Langley
      Pages 120-137

    7. Discovering Communicable Models from Earth Science Data

      • Mark Schwabacher, Pat Langley, Christopher Potter, Steven Klooster, Alicia Torregrosa
      Pages 138-157

    8. Structure Discovery from Massive Spatial Data Sets Using Intelligent Simulation Tools

      • Feng Zhao, Chris Bailey-Kellogg, Xingang Huang, Iván Ordóñez
      Pages 158-174

    9. Computational Discovery in Pure Mathematics

      • Simon Colton
      Pages 175-201

  4. II Computational Scientific Discovery in Biomedicine

    1. Front Matter

      Pages 203-203
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    2. Automatic Computational Discovery of Chemical Reaction Networks Using Genetic Programming

      • John R. Koza, William Mydlowec, Guido Lanza, Jessen Yu, Martin A. Keane
      Pages 205-227

    3. Discovery of Genetic Networks Through Abduction and Qualitative Simulation

      • Blaž Zupan, Ivan Bratko, Janez Demšar, Peter Juvan, Adam Kuspa, John A. Halter et al.
      Pages 228-247

    4. Learning Qualitative Models of Physical and Biological Systems

      • Simon M. Garrett, George M. Coghill, Ashwin Srinivasan, Ross D. King
      Pages 248-272

    5. Logic and the Automatic Acquisition of Scientific Knowledge: An Application to Functional Genomics

      • Ross D. King, Andreas Karwath, Amanda Clare, Luc Dehaspe
      Pages 273-289

    6. Drug Discovery as an Example of Literature-Based Discovery

      • Marc Weeber
      Pages 290-306

    7. Literature Based Discovery Support System and Its Application to Disease Gene Identification

      • Dimitar Hristovski, Borut Peterlin, Sašo Džeroski, Janez Stare
      Pages 307-326

  5. Back Matter

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Keywords

About this book

Advances in technology have enabled the collection of data from scientific observations, simulations, and experiments at an ever-increasing pace. For the scientist and engineer to benefit from these enhanced data collecting capabilities, it is becoming clear that semi-automated data analysis techniques must be applied to find the useful information in the data. Computational scientific discovery methods can be used to this end: they focus on applying computational methods to automate scientific activities, such as finding laws from observational data. In contrast to mining scientific data, which focuses on building highly predictive models, computational scientific discovery puts a strong emphasis on discovering knowledge represented in formalisms used by scientists and engineers, such as numeric equations and reaction pathways.

This state-of-the-art survey provides an introduction to computational approaches to the discovery of scientific knowledge and gives an overview of recent advances in this area, including techniques and applications in environmental and life sciences. The 15 articles presented are partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March 2001. More representative coverage of recent research in computational scientific discovery is achieved by a significant number of additional invited contributions.

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