Ontologies for Bioinformatics (Hardcover)

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Ontologies for Bioinformatics (Hardcover)

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內容描述

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Description:

Recent advances in biotechnology, spurred by the Human Genome
Project, have resulted in the accumulation of vast amounts of new data.
Ontologies -- computer-readable, precise formulations of concepts (and the
relationship among them) in a given field -- are a critical framework for
coping with the exponential growth of valuable biological data generated by
high-output technologies. This book introduces the key concepts and
applications of ontologies and ontology languages in bioinformatics and will
be an essential guide for bioinformaticists, computer scientists, and life
science researchers.The three parts of Ontologies for
Bioinformatics ask, and answer, three pivotal questions: what ontologies
are; how ontologies are used; and what ontologies could be (which focuses on
how ontologies could be used for reasoning with uncertainty). The authors
first introduce the notion of an ontology, from hierarchically organized
ontologies to more general network organizations, and survey the best-known
ontologies in biology and medicine. They show how to construct and use
ontologies, classifying uses into three categories: querying, viewing, and
transforming data to serve diverse purposes. Contrasting deductive, or
Boolean, logic with inductive reasoning, they describe the goal of a synthesis
that supports both styles of reasoning. They discuss Bayesian networks as a
way of expressing uncertainty, describe data fusion, and propose that the
World Wide Web can be extended to support reasoning with uncertainty. They
call this inductive reasoning web the Bayesian web.Kenneth Baclawski
is Associate Professor of Computer Science at Northeastern
University.Tianhua Niu is Assistant Professor of Medicine at Harvard
Medical School and Director of Bioinformatics, Division of Preventive
Medicine, at Brigham and Women's Hospital, Boston.

 
 
Table of Contents:

Preface
xi

I
Introduction to Ontologies
1

1
Hierarchies and Relationships
3

2
XML
Semantics
35

3
Rules
and Inference
51

4
The
Semantic Web and Bioinformatics Applications
61

5
Survey
of Ontologies in Bioinformatics
89

II
Building and Using Ontologies
127

6
Information Retrieval
129

7
Sequence Similarity Searching Tools
155

8
Query
Languages
175

9
The
Transformation Process
187

10
Transforming with Traditional Programming
Languages
203

11
The
XML Transformation Language
261

12
Building Bioinformatics Ontologies
281

III
Reasoning with Uncertainty
319

13
Inductive vs. Deductive Reasoning
321

14
Bayesian Networks
331

15
Combining Information
355

16
The
Bayesian Web
369

17
Answers to Selected Exercises
379

References
393

Index
413

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