Excerpt

This report by the Committee on Frontiers at the Interface of Computing and Biology seeks to establish the intellectual legitimacy of a fundamentally cross-disciplinary collaboration between biologists and computer scientists. That is, while some universities are increasingly favorable to research at the intersection, life science researchers at other universities are strongly impeded in their efforts to collaborate. This report addresses these impediments and describes some strategies for overcoming them.

Contents

• The National Academies
• Committee on Frontiers at the Interface of Computing and Biology
• Computer Science and Telecommunications Board
• Preface
• Acknowledgment of Reviewers
• Executive Summary
  • COMPUTING'S IMPACT ON BIOLOGY
  • BIOLOGY'S IMPACT ON COMPUTING
  • ILLUSTRATIVE PROBLEM DOMAINS AT THE BIOCOMP INTERFACE
  • THE ROLE OF ORGANIZATION AND INFRASTRUCTURE IN CREATING OPPORTUNITIES AT THE INTERFACE
  • FINDINGS AND RECOMMENDATIONS
  • CLOSING THOUGHTS
• 1. Introduction
  • 1.1 EXCITEMENT AT THE INTERFACE OF COMPUTING AND BIOLOGY
  • 1.2 PERSPECTIVES ON THE BIOCOMP INTERFACE
  • 1.3 Imagine What's Next
  • 1.4 SOME RELEVANT HISTORY IN BUILDING THE INTERFACE
  • 1.5 BACKGROUND, ORGANIZATION, AND APPROACH OF THIS REPORT
• 2. 21st Century Biology
  • 2.1 WHAT KIND OF SCIENCE?
  • 2.2 TOWARD A BIOLOGY OF THE 21ST CENTURY
  • 2.3 ROLES FOR COMPUTING AND INFORMATION TECHNOLOGY IN BIOLOGY
  • 2.4 CHALLENGES TO BIOLOGICAL EPISTEMOLOGY
• 3. On the Nature of Biological Data
  • 3.1 DATA HETEROGENEITY
  • 3.2 DATA IN HIGH VOLUME
  • 3.3 DATA ACCURACY AND CONSISTENCY
  • 3.4 DATA ORGANIZATION
  • 3.5 DATA SHARING
  • 3.6 DATA INTEGRATION
  • 3.7 DATA CURATION AND PROVENANCE
• 4. Computational Tools
  • 4.1 THE ROLE OF COMPUTATIONAL TOOLS
  • 4.2 TOOLS FOR DATA INTEGRATION
  • 4.3 DATA PRESENTATION
  • 4.4 ALGORITHMS FOR OPERATING ON BIOLOGICAL DATA
  • 4.5 DEVELOPING COMPUTATIONAL TOOLS
• 5. Computational Modeling and Simulation as Enablers for Biological Discovery
  • 5.1 ON MODELS IN BIOLOGY
  • 5.2 WHY BIOLOGICAL MODELS CAN BE USEFUL
  • 5.3 TYPES OF MODELS
  • 5.4 MODELING AND SIMULATION IN ACTION
  • 5.5 TECHNICAL CHALLENGES RELATED TO MODELING
• 6. A Computational and Engineering View of Biology
  • 6.1 BIOLOGICAL INFORMATION PROCESSING
  • 6.2 AN ENGINEERING PERSPECTIVE ON BIOLOGICAL ORGANISMS
  • 6.3 A COMPUTATIONAL METAPHOR FOR BIOLOGY
• 7. Cyberinfrastructure and Data Acquisition
  • 7.1 CYBERINFRASTRUCTURE FOR 21ST CENTURY BIOLOGY
  • 7.2 DATA ACQUISITION AND LABORATORY AUTOMATION
• 8. Biological Inspiration for Computing
  • 8.1 THE IMPACT OF BIOLOGY ON COMPUTING
  • 8.2 EXAMPLES OF BIOLOGY AS A SOURCE OF PRINCIPLES FOR COMPUTING
  • 8.3 BIOLOGY AS IMPLEMENTER OF MECHANISMS FOR COMPUTING
  • 8.4 BIOLOGY AS PHYSICAL SUBSTRATE FOR COMPUTING
• 9. Illustrative Problem Domains at the Interface of Computing and Biology
  • 9.1 WHY PROBLEM-FOCUSED RESEARCH?
  • 9.2 CELLULAR AND ORGANISMAL MODELING
  • 9.3 A SYNTHETIC CELL WITH PHYSICAL FORM
  • 9.4 NEURAL INFORMATION PROCESSING AND NEURAL PROSTHETICS
  • 9.5 EVOLUTIONARY BIOLOGY
  • 9.6 COMPUTATIONAL ECOLOGY
  • 9.7 GENOME-ENABLED INDIVIDUALIZED MEDICINE
  • 9.8 A DIGITAL HUMAN ON WHICH A SURGEON CAN OPERATE VIRTUALLY
  • 9.9 COMPUTATIONAL THEORIES OF SELF-ASSEMBLY AND SELF-MODIFICATION
  • 9.10 A THEORY OF BIOLOGICAL INFORMATION AND COMPLEXITY
• 10. Culture and Research Infrastructure
  • 10.1 SETTING THE CONTEXT
  • 10.2 ORGANIZATIONS AND INSTITUTIONS
  • 10.3 BARRIERS
• 11. Conclusions and Recommendations
  • 11.1 DISCIPLINARY PERSPECTIVES
  • 11.2 MOVING FORWARD
  • 11.3 THE SPECIAL SIGNIFICANCE OF EDUCATIONAL INNOVATION AT THE BIOCOMP INTERFACE
  • 11.4 RECOMMENDATIONS FOR RESEARCH FUNDING AGENCIES
  • 11.5 CONCLUSIONS REGARDING INDUSTRY
  • 11.6 CLOSING THOUGHTS
• Appendixes
  • A The Secrets of Life: A Mathematician's Introduction to Molecular Biology
  • B Challenge Problems in Bioinformatics and Computational Biology from Other Reports
  • C Biographies of Committee Members and Staff
  • D Workshop Participants
• What Is CSTB?

Support for this project was provided by the Defense Advanced Research Projects Agency under Contract No. MDA972-00-1-0005, the National Science Foundation under Contract No. DBI-0094528, the Department of Health and Human Services/National Institutes of Health (including the National Institute of General Medical Sciences and the National Center for Research Resources) under Contract No. N01-OD-4-2139, the Department of Energy under Contract No. DE-FG02-02ER63336, the Department of Energy’s Office of Science (BER) under Interagency Agreement No. DE-FG02-04ER63934, and National Research Council funds. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the organizations or agencies that provided support for the project.

NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The members of the committee responsible for the report were chosen for their special competences and with regard for appropriate balance.