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Data Integration in the Life Sciences

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Cover of 'Data Integration in the Life Sciences'

Table of Contents

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    Book Overview
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    Chapter 1 An Ontology-Driven Framework for Data Transformation in Scientific Workflows
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    Chapter 2 PROVA: Rule-Based Java-Scripting for a Bioinformatics Semantic Web
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    Chapter 3 Process Based Data Logistics: a Solution for Clinical Integration Problems
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    Chapter 4 Domain-Specific Concepts and Ontological Reduction within a Data Dictionary Framework
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    Chapter 5 A Universal Character Model and Ontology of Defined Terms for Taxonomic Description
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    Chapter 6 On the Application of Formal Principles to Life Science Data: a Case Study in the Gene Ontology
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    Chapter 7 Index-Driven XML Data Integration to Support Functional Genomics
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    Chapter 8 Heterogeneous Data Integration with the Consensus Clustering Formalism
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    Chapter 9 LinkSuite TM : Formally Robust Ontology-Based Data and Information Integration
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    Chapter 10 BioDataServer : an Applied Molecular Biological Data Integration Service
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    Chapter 11 Columba : Multidimensional Data Integration of Protein Annotations
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    Chapter 12 On the Integration of a Large Number of Life Science Web Databases
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    Chapter 13 Efficient Techniques to Explore and Rank Paths in Life Science Data Sources
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    Chapter 14 Links and Paths through Life Sciences Data Sources
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    Chapter 15 Pathway and Protein Interaction Data: from XML to FDM Database
Attention for Chapter 8: Heterogeneous Data Integration with the Consensus Clustering Formalism
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Chapter title
Heterogeneous Data Integration with the Consensus Clustering Formalism
Chapter number 8
Book title
Data Integration in the Life Sciences
Published by
Springer, Berlin, Heidelberg, March 2004
DOI 10.1007/978-3-540-24745-6_8
Book ISBNs
978-3-54-021300-0, 978-3-54-024745-6
Authors

Vladimir Filkov, Steven Skiena

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 3%
Italy 1 3%
Australia 1 3%
Unknown 31 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Researcher 7 21%
Professor > Associate Professor 4 12%
Student > Master 3 9%
Student > Postgraduate 2 6%
Other 6 18%
Unknown 3 9%
Readers by discipline Count As %
Computer Science 21 62%
Engineering 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Agricultural and Biological Sciences 2 6%
Mathematics 1 3%
Other 2 6%
Unknown 3 9%