1st Edition

Managing Scientific Data

Print ISBN: 9781558608290
eBook ISBN: 9780080527987
Imprint: Morgan Kaufmann
Published Date: 18th July 2003
Page Count: 441
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Life science data integration and interoperability is one of the most challenging problems facing bioinformatics today. In the current age of the life sciences, investigators have to interpret many types of information from a variety of sources: lab instruments, public databases, gene expression profiles, raw sequence traces, single nucleotide polymorphisms, chemical screening data, proteomic data, putative metabolic pathway models, and many others. Unfortunately, scientists are not currently able to easily identify and access this information because of the variety of semantics, interfaces, and data formats used by the underlying data sources.

Bioinformatics: Managing Scientific Data tackles this challenge head-on by discussing the current approaches and variety of systems available to help bioinformaticians with this increasingly complex issue. The heart of the book lies in the collaboration efforts of eight distinct bioinformatics teams that describe their own unique approaches to data integration and interoperability. Each system receives its own chapter where the lead contributors provide precious insight into the specific problems being addressed by the system, why the particular architecture was chosen, and details on the system's strengths and weaknesses. In closing, the editors provide important criteria for evaluating these systems that bioinformatics professionals will find valuable.

Key Features

  • Provides a clear overview of the state-of-the-art in data integration and interoperability in genomics, highlighting a variety of systems and giving insight into the strengths and weaknesses of their different approaches.
  • Discusses shared vocabulary, design issues, complexity of use cases, and the difficulties of transferring existing data management approaches to bioinformatics systems, which serves to connect computer and life scientists.
  • Written by the primary contributors of eight reputable bioinformatics systems in academia and industry including: BioKris, TAMBIS, K2, GeneExpress, P/FDM, MBM, SDSC, SRS, and DiscoveryLink.


Bioinformaticians involved in data management (development, design, management, etc) at corporations and research companies. CS and life science students in bioinformatics programs.

Table of Contents

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


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© Morgan Kaufmann 2004
Morgan Kaufmann
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An exciting compilation that addresses the key issues in biological data management. -Sylvia Spengler, Lawrence Berkeley National Laboratory