عنوان

Data mining in biomedicine using ontologies /

(Number (ISBN

1596933712

(Number (ISBN

9781596933712

Erroneous ISBN

1596933704

Erroneous ISBN

9781596933705

Number

b746629

Title Proper

Data mining in biomedicine using ontologies /

General Material Designation

[Book]

First Statement of Responsibility

Mihail Popescu, Dong Xu, editors.

Place of Publication, Distribution, etc.

Norwood, MA :

Name of Publisher, Distributor, etc.

Artech House,

Date of Publication, Distribution, etc.

©2009.

Specific Material Designation and Extent of Item

1 online resource (xv, 262 pages) :

Other Physical Details

illustrations.

Series Title

Artech House series bioinformatics & biomedical imaging

Text of Note

Includes bibliographical references and index.

Text of Note

Data Mining in Biomedicine Using Ontologies; Contents; Foreword; Preface; Chapter 1 Introduction to Ontologies; 1.1 Introduction; 1.2 History of Ontologies in Biomedicine; 1.2.1 The Philosophical Connection; 1.2.2 Recent Definition in Computer Science; 1.2.3 Origins of Bio-Ontologies; 1.2.4 Clinical and Medical Terminologies; 1.2.5 Recent Advances in Computer Science; 1.3 Form and Function of Ontologies; 1.3.1 Basic Components of Ontologies; 1.3.2 Components for Humans, Components for Computers; 1.3.3 Ontology Engineering; 1.4 Encoding Ontologies; 1.4.1 The OBO Format and the OBO Consortium

Text of Note

1.4.2 OBO-Edit-The Open Biomedical Ontologies Editor 1.4.3 OWL and RDF/XML; 1.4.4 Protégé-An OWL Ontology Editor; 1.5 Spotlight on GO and UMLS; 1.5.1 The Gene Ontology; 1.5.2 The Unified Medical Language System; 1.6 Types and Examples of Ontologies; 1.6.1 Upper Ontologies; 1.6.2 Domain Ontologies; 1.6.3 Formal Ontologies; 1.6.4 Informal Ontologies; 1.6.5 Reference Ontologies; 1.6.6 Application Ontologies; 1.6.7 Bio-Ontologies; 1.7 Conclusion; References; Chapter 2 Ontological Similarity Measures; 2.1 Introduction; 2.1.1 History; 2.1.2 Tversky's Parameterized Ratio Model of Similarity

Text of Note

2.1.3 Aggregation in Similarity Assessment 2.2 Traditional Approaches to Ontological Similarity; 2.2.1 Path-Based Measures; 2.2.2 Information Content Measures; 2.2.3 A Relationship Between Path-Based and Information-Content Measures; 2.3 New Approaches to Ontological Similarity; 2.3.1 Entity Class Similarity in Ontologies; 2.3.2 Cross-Ontological Similarity Measures; 2.3.3 Exploiting Common Disjunctive Ancestors; 2.4 Conclusion; References; Chapter 3 Clustering with Ontologies; 3.1 Introduction; 3.2 Relational Fuzzy C-Means (NERFCM); 3.3 Correlation Cluster Validity (CCV)

Text of Note

3.4 Ontological SOM (OSOM)3.5 Examples of NERFCM, CCV, and OSOM Applications; 3.5.1 Test Dataset; 3.5.2 Clustering of the GPD 194 Dataset Using NERFCM; 3.5.3 Determining the Number of Clusters of GPD 194 Dataset Using CCV; 3.5.4 GPD 194 Analysis Using OSOM; 3.6 Conclusion; References; Chapter 4 Analyzing and Classifying Protein Family Data Using OWL Reasoning; 4.1 Introduction; 4.1.1 Analyzing Sequence Data; 4.1.2 The Protein Phosphatase Family; 4.2 Methods; 4.2.1 The Phosphatase Classification Pipeline; 4.2.2 The Datasets; 4.2.3 The Phosphatase Ontology; 4.3 Results

Text of Note

4.3.1 Protein Phosphatases in Humans 4.3.2 Results from the Analysis of A. Fumigatus; 4.3.3 Ontology System Versus A. Fumigatus Automated Annotation Pipeline; 4.4 Ontology Classification in the Comparative Analysis of Three Protozoan Parasites-A Case Study; 4.4.1 TriTryps Diseases; 4.4.2 TriTryps Protein Phosphatases; 4.4.3 Methods for the Protozoan Parasites; 4.4.4 Sequence Analysis Results from the TriTryps Phosphatome Study; 4.4.5 Evaluation of the Ontology Classification Method; 4.5 Conclusion; References; Chapter 5 GO-Based Gene Function and Network Characterization; 5.1 Introduction

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Text of Note

Presently, a growing number of ontologies are being built and used for annotating data in biomedical research. Thanks to the tremendous amount of data being generated, ontologies are now being used in numerous ways, including connecting different databases, refining search capabilities, interpreting experimental/clinical data, and inferring knowledge. This cutting-edge resource introduces you to latest developments in bio-ontologies. The book provides you with the theoretical foundations and examples of ontologies, as well as applications of ontologies in biomedicine, from molecular levels to clinical levels. You also find details on technological infrastructure for bio-ontologies. This comprehensive, one-stop volume presents a wide range of practical bio-ontology information, offering you detailed guidance in the clustering of biological data, protein classification, gene and pathway prediction, and text mining. More than 160 illustrations support key topics throughout the book.

Title

Data mining in biomedicine using ontologies.

International Standard Book Number

9781596933705

Bioinformatics.

Data mining.

Medical informatics.

Ontologies (Information retrieval)

Computational Biology.

Bioinformatics.

Data mining.

MEDICAL-- Allied Health Services-- Medical Technology.

MEDICAL-- Biotechnology.

MEDICAL-- Family & General Practice.

Medical informatics.

MEDICAL-- Lasers in Medicine.

Ontologies (Information retrieval)

TECHNOLOGY & ENGINEERING-- Biomedical.

MED-- 003040

MED-- 009000

MED-- 029000

MED-- 048000

TEC-- 059000

Number

Edition

Class number

Book number

Class number

Class number

Book Number

Popescu, Mihail,1962-

Xu, Dong,1965-

Date of Transaction

20201204064554.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y