Ontologies for Bioinformatics (Hardcover)

Kenneth Baclawski, Tianhua Niu

  • 出版商: The MIT Press
  • 出版日期: 2005-09-23
  • 定價: $1,390
  • 售價: 5.0$695
  • 語言: 英文
  • 頁數: 440
  • 裝訂: Hardcover
  • ISBN: 0262025914
  • ISBN-13: 9780262025911
  • 相關分類: Bioinformatics 生物資訊

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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