| Description |
xxi, 441 pages : illustrations ; 24 cm |
| Series |
The Morgan Kaufmann series in multimedia information and systems |
|
Morgan Kaufmann series in multimedia information and systems.
|
| Contents |
Machine derived contents note: Table of contents for Bioinformatics : managing scientific data / edited by Zoâe Lacroix and Terence Critchlow. -- Bibliographic record and links to related information available from the Library of Congress catalog -- Information from electronic data provided by the publisher. May be incomplete or contain other coding. -- 1 Introduction -- Zoe Lacroix and Terence Critchlow -- 1.1 Overview -- 1.2 Problem and Scope -- 1.3 Biological Data Integration -- 1.4 Developing a Biological Data Integration System -- 1.4.1 Specifications -- 1.4.2 Translating Specifications into a Technical Approach -- 1.4.3 Development Process -- 1.4.4 Evaluation of the System -- References -- 2 Challenges Faced in the Integration of Biological -- Information -- Su Yun Chung and John C. Wooley -- 2.1 The Life Science Discovery Process -- 2.2 An Information Integration Environment for Life Science Discovery -- 2.3 The Nature of Biological Data -- 2.3.1 Diversity -- 2.3.2 Variability -- 2.4 Data Sources in Life Science -- 2.4.1 Biological Databases Are Autonomous -- 2.4.2 Biological Databases Are Heterogeneous in Data Formats -- 2.4.3 Biological Data Sources Are Dynamic -- 2.4.4 Computational Analysis Tools Require Specific -- Input/Output Formats and Broad Domain Knowledge -- 2.5 Challenges in Information Integration -- 2.5.1 Data Integration -- 2.5.2 Meta-Data Specification -- 2.5.3 Data Provenance and Data Accuracy -- 2.5.4 Ontology -- 2.5.5 Web Presentations -- Conclusion -- References -- 3 A Practitioner's Guide to Data Management and Data -- Integration in Bioinformatics -- Barbara A. Eckman -- 3.1 Introduction -- 3.2 Data Management in Bioinformatics -- 3.2.1 Data Management Basics -- 3.2.2 Two Popular Data Management Strategies -- and Their Limitations -- 3.2.3 Traditional Database Management -- 3.3 Dimensions Describing the Space of Integration Solutions -- 3.3.1 A Motivating Use Case for Integration -- 3.3.2 Browsing vs. Querying -- 3.3.3 Syntactic vs. Semantic Integration -- 3.3.4 Warehouse vs. Federation -- 3.3.5 Declarative vs. Procedural Access -- 3.3.6 Generic vs. Hard-Coded -- 3.3.7 Relational vs. Non-Relational Data Model -- 3.4 Use Cases of Integration Solutions -- 3.4.1 Browsing-Driven Solutions -- 3.4.2 Data Warehousing Solutions -- 3.4.3 Federated Database Systems Approach -- 3.4.4 Semantic Data Integration -- 3.5 Strengths and Weaknesses of the Various Approaches to Integration -- 3.5.1 Browsing and Querying: Strengths and Weaknesses -- 3.5.2 Warehousing and Federation: Strengths and Weaknesses -- 3.5.3 Procedural Code and Declarative Query Language: -- Strengths and Weaknesses -- 3.5.4 Generic and Hard-Coded Approaches: -- Strengths and Weaknesses -- 3.5.5 Relational and Non-Relational Data Models: Strengths -- and Weaknesses -- 3.5.6 Conclusion: A Hybrid Approach to Integration Is Ideal -- 3.6 Tough Problems in Bioinformatics Integration -- 3.6.1 Semantic Query Planning Over Web Data Sources -- 3.6.2 Schema Management -- 3.7 Summary -- Acknowledgments -- References -- 4 Issues to Address While Designing a Biological -- Information System -- Zoe Lacroix -- 4.1 Legacy -- 4.1.1 Biological Data -- 4.1.2 Biological Tools and Workflows -- 4.2 A Domain in Constant Evolution -- 4.2.1 Traditional Database Management and Changes -- 4.2.2 Data Fusion -- 4.2.3 Fully Structured vs. Semi-Structured -- 4.2.4 Scientific Object Identity -- 4.2.5 Concepts and Ontologies -- 4.3 Biological Queries -- 4.3.1 Searching and Mining -- 4.3.2 Browsing -- 4.3.3 Semantics of Queries -- 4.3.4 Tool-Driven vs. Data-Driven Integration -- 4.4 Query Processing -- 4.4.1 Biological Resources -- 4.4.2 Query Planning -- 4.4.3 Query Optimization -- 4.5 Visualization -- 4.5.1 Multimedia Data -- 4.5.2 Browsing Scientific Objects -- 4.6 Conclusion -- Acknowledgments -- References -- 5 SRS: An Integration Platform for Databanks -- and Analysis Tools in Bioinformatics -- Thure Etzold, Howard Harris, and Simon Beaulah -- 5.1 Integrating Flat File Databanks -- 5.1.1 The SRS Token Server -- 5.1.2 Subentry Libraries -- 5.2 Integration of XML Databases -- 5.2.1 What Makes XML Unique? -- 5.2.2 How Are XML Databanks Integrated into SRS? -- 5.2.3 Overview of XML Support Features -- 5.2.4 How Does SRS Meet the Challenges of XML? -- 5.3 Integrating Relational Databases -- 5.3.1 Whole Schema Integration -- 5.3.2 Capturing the Relational Schema -- 5.3.3 Selecting a Hub Table -- 5.3.4 Generation of SQL -- 5.3.5 Restricting Access to Parts of the Schema -- 5.3.6 Query Performance to Relational Databases -- 5.3.7 Viewing Entries from a Relational Databank -- 5.3.8 Summary -- 5.4 The SRS Query Language -- 5.4.1 SRS Fields -- 5.5 Linking Databanks -- 5.5.1 Constructing Links -- 5.5.2 The Link Operators -- 5.6 The Object Loader -- 5.6.1 Creating Complex and Nested Objects -- 5.6.2 Support for Loading from XML Databanks -- 5.6.3 Using Links to Create Composite Structures -- 5.6.4 Exporting Objects to XML -- 5.7 Scientific Analysis Tools -- 5.7.1 Processing of Input and Output -- 5.7.2 Batch Queues -- 5.8 Interfaces to SRS -- 5.8.1 The Web Interface -- 5.8.2 SRS Objects -- 5.8.3 SOAP and Web Services -- 5.9 Automated Server Maintenance with SRS Prisma -- 5.10 Conclusion -- References -- 6 The Kleisli Query System as a Backbone for -- Bioinformatics Data Integration and Analysis -- Jing Chen, Su Yun Chung, and Limsoon Wong -- 6.1 Motivating Example -- 6.2 Approach -- 6.3 Data Model and Representation -- 6.4 Query Capability -- 6.5 Warehousing Capability -- 6.6 Data Sources -- 6.7 Optimizations -- 6.7.1 Monadic Optimizations -- 6.7.2 Context-Sensitive Optimizations -- 6.7.3 Relational Optimizations -- 6.8 User Interfaces -- 6.8.1 Programming Language Interface -- 6.8.2 Graphical Interface -- 6.9 Other Data Integration Technologies -- 6.9.1 Srs -- 6.9.2 DiscoveryLink -- 6.9.3 Object-Protocol Model (OPM) -- 6.10 Conclusions -- References -- 7 Complex Query Formulation Over Diverse -- Information Sources in TAMBIS -- Robert Stevens, Carole Goble, Norman W. Paton, -- Sean Bechhofer, Gary Ng, Patricia Baker, and Andy Brass -- 7.1 The Ontology -- 7.2 The User Interface -- 7.2.1 Exploring the Ontology -- 7.2.2 Constructing Queries -- 7.2.3 The Role of Reasoning in Query Formulation -- 7.3 The Query Processor -- 7.3.1 The Sources and Services Model -- 7.3.2 The Query Planner -- 7.3.3 The Wrappers -- 7.4 Related Work -- x Contents -- 7.4.1 Information Integration in Bioinformatics -- 7.4.2 Knowledge Based Information Integration -- 7.4.3 Biological Ontologies -- 7.5 Current and Future Developments in TAMBIS -- 7.5.1 Summary -- Acknowledgments -- References -- 8 The Information Integration System K2 -- Val Tannen, Susan B. Davidson, and Scott Harker -- 8.1 Approach -- 8.2 Data Model and Languages -- 8.3 An Example -- 8.4 Internal Language -- 8.5 Data Sources -- 8.6 Query Optimization -- 8.7 User Interfaces -- 8.8 Scalability -- 8.9 Impact -- 8.10 Summary -- Acknowledgments -- References -- 9 P/FDM Mediator for a Bioinformatics Database -- Federation -- Graham J. L. Kemp and Peter M. D. Gray -- 9.1 Approach -- 9.1.1 Alternative Architectures for Integrating Databases -- 9.1.2 The Functional Data Model -- 9.1.3 Schemas in the Federation -- 9.1.4 Mediator Architecture -- 9.1.5 Example -- 9.1.6 Query Capabilities -- 9.1.7 Data Sources -- 9.2 Analysis -- 9.2.1 Optimization -- 9.2.2 User Interfaces -- 9.2.3 Scalability -- 9.3 Conclusions -- Acknowledgment -- References -- 10 Integration Challenges in Gene Expression Data -- Management -- Victor M. Markowitz, John Campbell, I-Min A. Chen, -- Anthony Kosky, Krishna Palaniappan, -- and Thodoros Topaloglou -- 10.1 Gene Expression Data Management: Background -- 10.1.1 Gene Expression Data Spaces -- 10.1.2 Standards: Benefits and Limitations -- 10.2 The GeneExpress System -- 10.2.1 GeneExpress System Components -- 10.2.2 GeneExpress Deployment and Update Issues -- 10.3 Managing Gene Expression Data: Integration Challenges -- 10.3.1 Gene Expression Data: Array Versions -- 10.3.2 Gene Expression Data: Algorithms and Normalization -- 10.3.3 Gene Expression Data: Variability -- 10.3.4 Sample Data -- 10.3.5 Gene Annotations -- 10.4 Integrating Third-Party Gene Expression Data in GeneExpress -- 10.4.1 Data Exchange Formats -- 10.4.2 Structural Data Transformation Issues -- 10.4.3 Semantic Data Mapping Issues -- 10.4.4 Data Loading Issues -- 10.4.5 Update Issues -- 10.5 Summary -- Acknowledgments -- Trademarks -- References -- 11 DiscoveryLink -- Laura M. Haas, Barbara A. Eckman, Prasad Kodali, -- Eileen T. Lin, Julia E. Rice, and Peter M. Schwarz -- 11.1 Approach -- 11.1.1 Architecture -- 11.1.2 Registration -- 11.2 Query Processing Overview -- 11.2.1 Query Optimization -- 11.2.2 An Example -- 11.2.3 Determining Costs -- 11.3 Ease of Use, Scalability, and Performance -- 11.4 Conclusions -- References -- 12 A Model-Based Mediator System for Scientific Data -- Management -- Bertram Ludascher, Amarnath Gupta, -- and Maryann E. Martone -- 12.1 Background -- 12.2 Scientific Data Integration Across Multiple Worlds: Examples -- and Challenges from the Neurosciences -- 12.2.1 From Terminology and Static Knowledge -- to Process Context -- 12.3 Model-Based Mediation -- 12.3.1 Model-Based Mediation: The Protagonists -- 12.3.2 Conceptual Models and Registration -- of Sources at the Mediator -- 12.3.3 Interplay Between Mediator and Sources -- 12.4 Knowledge Representation for Model-Based Mediation -- 12.4.1 Domain Maps -- 12.4.2 Process Maps -- 12.5 M |
| Notes |
Formerly CIP. Uk |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Bioinformatics.
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| Author |
Lacroix, Zoé.
|
|
Critchlow, Terence.
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| LC no. |
2003044603 |
| ISBN |
155860829X paperback alkaline paper |
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