Details

Database and Literature Integration.- Semantic Web Approach to Database Integration in the Life Sciences.- Querying Semantic Web Contents.- Knowledge Acquisition from the Biomedical Literature.- Ontologies in the Life Sciences.- Biological Ontologies.- Clinical Ontologies for Discovery Applications.- Ontology Engineering for Biological Applications.- The Evaluation of Ontologies.- OWL for the Novice: A Logical Perspective.- Ontology Visualization.- Techniques for Ontology Visualization.- On Visualization of OWL Ontologies.- Ontologies in Action.- Applying OWL Reasoning to Genomic Data.- Can Semantic Web Technologies Enable Translational Medicine?.- Ontology Design for Biomedical Text Mining.- Using Distributed Knowledge.- Sembowser - Semantic Biological Web Services Registry.- Agent Technologies in the Life Sciences.- Knowledge Discovery for Biology with Taverna.- On the Success of the Semantic Web in the Life Sciences.- Factors Influencing the Adoption of the Semantic Web in the Life Sciences.- Semantic Web Standards: Legal and Social Issues and Implications.

<P>Christopher Baker is a Principle Investigator at the Knowledge Discovery Department of the Institute for Infocomm Research (I<SUP>2</SUP>R), a member of the Agency for Science, Technology and Research (A*STAR) in Singapore. Dr Baker was formerly Bioinformatics Project Manager of the Génome Québec funded project, ’Ontologies, the semantic web and intelligent systems for genomics’ where he coordinated the application of knowledge management technologies to fungal genomic data sets. Prior to this he was Group Leader In-silico Discovery at Ecopia BioSciences Inc. where he masterminded key portions of the DecipherIT™ bioinformatics software suite and managed the genomic annotation team. Dr Baker received post doctoral training at Iogen Corporation and the University of Toronto after completing his Ph. D. studies in Environmental Microbiology and Enzymology at the University of Wales, Cardiff, UK.</P>
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<P>Dr. Cheung is currently an Associate Professor at the Center for Medical Informatics, Yale University School of Medicine. Dr. Cheung is a bioinformatician with a Ph.D. in Computer Science. He has established a broad base of collaboration with life scientists, computational biologists, and computer scientists. Dr. Cheung has published extensively in the field of bioinformatics. He is one of the core faculty members in the Yale Ph.D. Program in Computational Biology and Bioinformatics. In addition, he is a Principal Investigator of two research grants (one was awarded by the National Institutes of Health and the other was awarded by the National Science Foundation). Dr. Cheung’s research interests include biological database and tool integration. Recently, Dr. Cheung has embarked on the research and development of Semantic Web in the bioscience domain. </P>

<P>The Semantic Web is now a research discipline in its own right and commercial interest in applications of Semantic Web technologies is strong. The advantages of the Semantic Web lie in its ability to present and provide access to complex knowledge in a standardized form making interoperability between distributed databases and middleware achievable. <BR><BR>Life Scientists have much to gain from the emergence of the Semantic Web since their work is strongly knowledge-based. Unambiguous, semantically-rich, structured declarations of information have long been a fundamental cornerstone of scientific discourse. To have such information available in machine-readable form makes a whole new generation of scientific software possible. The value that the Semantic Web offers to the Life Sciences is currently under appreciated. A pedagogical oasis is required for interested scientists and bioinformatics professionals, where they can learn about and draw inspiration from the Semantic Web and its component technologies. In this context this book seeks to offer students, researchers, and professionals a glimpse of the technology, its capabilities and the reach of its current implementation in the Life Sciences. This collection of representative topics, written by leading experts, documents important and encouraging first steps showing the utility of the Semantic Web to Life Science research. <BR><BR><STRONG>Semantic Web: Revolutionizing Knowledge Discovery in Life Sciences</STRONG> is divided into six parts that cover the topics of: knowledge integration, knowledge representation, knowledge visualization, utilization of formal knowledge representations, and access to distributed knowledge. The final part considers the viability of the semantic web in life science and the legal challenges that will impact on its establishment. <BR><BR>This book may be approached from technical, scientific or application specific perspectives. Component technologies of the Semantic Web (including RDF databases, ontologies, ontological languages, agent systems and web services) are described throughout the book. They are the basic building blocks for creating the Semantic Web infrastructure. Other technologies, such as natural language processing and text mining, which are becoming increasingly important to the Semantic Web, are also discussed. Scientists reading the book will see that the complex needs of biology and medicine are being addressed. Moreover, pioneering Life Scientists have joined forces with Semantic Web developers to build valuable semantic resources for the scientific community. Different areas of computer science (e.g., artificial intelligence, database integration, and visualization) are also being recruited to advance this vision. The ongoing synergy between the Life Sciences and Computer Science is poised to deliver revolutionary discovery tools and new capabilities. <BR><BR>As well as providing the background material and critical evaluation criteria for the design and use of meaningful Semantic Web implementations a multitude of examples are provided. These illustrate the diversity of life science tasks that are benefiting from the use of Semantic Web infrastructure and serve to demonstrate the great potential of the Semantic Web in the Life Sciences.</P>

Covers topics ranging from database, ontology, visualization, to semantic web services and workflows Features the intersection of Semantic Web and Life Sciences Gives examples/scenarios illustrating different Semantic Web applications in the life science domain Discusses the limitations and obstacles that need to be overcome for Semantic Web to better meet the current and future needs of life science researchers Includes supplementary material: sn.pub/extras