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Author: John Hancock
Publisher: Frontiers Media SA
ISBN: 2889192776
Category : Biotechnology
Languages : en
Pages : 107
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Book Description
As the amount of biological information and its diversity accumulates massively there is a critical need to facilitate the integration of this data to allow new and unexpected conclusions to be drawn from it. The Semantic Web is a new wave of web- based technologies that allows the linking of data between diverse data sets via standardised data formats (“big data”). Semantic Biology is the application of semantic web technology in the biological domain (including medical and health informatics). The Special Topic encompasses papers in this very broad area, including not only ontologies (development and applications), but also text mining, data integration and data analysis making use of the technologies of the Semantic Web. Ontologies are a critical requirement for such integration as they allow conclusions drawn about biological experiments, or descriptions of biological entities, to be understandable and integratable despite being contained in different databases and analysed by different software systems. Ontologies are the standard structures used in biology, and more broadly in computer science, to hold standardized terminologies for particular domains of knowledge. Ontologies consist of sets of standard terms, which are defined and may have synonyms for ease of searching and to accommodate different usages by different communities. These terms are linked by standard relationships, such as “is_a” (an eye “is_a” sense organ) or “part_of” (an eye is “part_of” a head). By linking terms in this way, more detailed, or granular, terms can be linked to broader terms, allowing computation to be carried out that takes these relationships into account.
Author: John Hancock
Publisher: Frontiers Media SA
ISBN: 2889192776
Category : Biotechnology
Languages : en
Pages : 107
Get Book
Book Description
As the amount of biological information and its diversity accumulates massively there is a critical need to facilitate the integration of this data to allow new and unexpected conclusions to be drawn from it. The Semantic Web is a new wave of web- based technologies that allows the linking of data between diverse data sets via standardised data formats (“big data”). Semantic Biology is the application of semantic web technology in the biological domain (including medical and health informatics). The Special Topic encompasses papers in this very broad area, including not only ontologies (development and applications), but also text mining, data integration and data analysis making use of the technologies of the Semantic Web. Ontologies are a critical requirement for such integration as they allow conclusions drawn about biological experiments, or descriptions of biological entities, to be understandable and integratable despite being contained in different databases and analysed by different software systems. Ontologies are the standard structures used in biology, and more broadly in computer science, to hold standardized terminologies for particular domains of knowledge. Ontologies consist of sets of standard terms, which are defined and may have synonyms for ease of searching and to accommodate different usages by different communities. These terms are linked by standard relationships, such as “is_a” (an eye “is_a” sense organ) or “part_of” (an eye is “part_of” a head). By linking terms in this way, more detailed, or granular, terms can be linked to broader terms, allowing computation to be carried out that takes these relationships into account.
Author: Peter N. Robinson
Publisher: CRC Press
ISBN: 1439836663
Category : Computers
Languages : en
Pages : 517
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Book Description
Introduction to Bio-Ontologies explores the computational background of ontologies. Emphasizing computational and algorithmic issues surrounding bio-ontologies, this self-contained text helps readers understand ontological algorithms and their applications. The first part of the book defines ontology and bio-ontologies. It also explains the importance of mathematical logic for understanding concepts of inference in bio-ontologies, discusses the probability and statistics topics necessary for understanding ontology algorithms, and describes ontology languages, including OBO (the preeminent language for bio-ontologies), RDF, RDFS, and OWL. The second part covers significant bio-ontologies and their applications. The book presents the Gene Ontology; upper-level ontologies, such as the Basic Formal Ontology and the Relation Ontology; and current bio-ontologies, including several anatomy ontologies, Chemical Entities of Biological Interest, Sequence Ontology, Mammalian Phenotype Ontology, and Human Phenotype Ontology. The third part of the text introduces the major graph-based algorithms for bio-ontologies. The authors discuss how these algorithms are used in overrepresentation analysis, model-based procedures, semantic similarity analysis, and Bayesian networks for molecular biology and biomedical applications. With a focus on computational reasoning topics, the final part describes the ontology languages of the Semantic Web and their applications for inference. It covers the formal semantics of RDF and RDFS, OWL inference rules, a key inference algorithm, the SPARQL query language, and the state of the art for querying OWL ontologies. Web Resource Software and data designed to complement material in the text are available on the book’s website: http://bio-ontologies-book.org The site provides the R Robo package developed for the book, along with a compressed archive of data and ontology files used in some of the exercises. It also offers teaching/presentation slides and links to other relevant websites. This book provides readers with the foundation to use ontologies as a starting point for new bioinformatics research projects or to support current molecular genetics research projects. By supplying a self-contained introduction to OBO ontologies and the Semantic Web, it bridges the gap between both fields and helps readers see what each can contribute to the analysis and understanding of biomedical data.
Author: Christopher J. O. Baker
Publisher: Springer Science & Business Media
ISBN: 0387484388
Category : Science
Languages : en
Pages : 449
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Book Description
This book introduces advanced semantic web technologies, illustrating their utility and highlighting their implementation in biological, medical, and clinical scenarios. It covers topics ranging from database, ontology, and visualization to semantic web services and workflows. The volume also details the factors impacting on the establishment of the semantic web in life science and the legal challenges that will impact on its proliferation.
Author: Bijan Parsia
Publisher: Wiley
ISBN: 9780470504963
Category : Medical
Languages : en
Pages : 400
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Book Description
This invaluable book covers the opportunities and challenges in building HCLS ontologies and looks at state of the art and future opportunities. Primarily focused on OWL2, the most popular ontology language, it utilizes case studies to help illustrate lessons learned through concrete examples. The definitive guide for the design and use of expressive bio-ontologies compatible with the rapidly evolving Semantic Web, this book will be the go-to resource for practicing professionals and researchers in the field.
Author: Daniel L. Cook
Publisher: CRC Press
ISBN: 0429892330
Category : Science
Languages : en
Pages : 241
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Book Description
This book introduces semantic representations of multiscale, multidomain physiological systems that link to qualitative reasoning and to quantitative analysis of biophysical processes in health and disease. Two major public health problems, diabetes and hypertension, serve as use-cases to illustrate the depth and rigor of such representations for logical inference and quantitative analysis. Central to this approach is the Ontology of Physics for Biology (OPB) that formally represents the foundations of classical physics and engineering system dynamics that are the basis for our understanding of biomedical entities, processes, and functional relationships. Furthermore, we introduce OPB-based software for annotating and abstracting available biosimulation models for reuse, recombination, and for archiving of physics-based biomedical knowledge. We have formalized and leveraged physics-based biological knowledge as a working view of physiology and biophysics from three distinct perspectives: (1) biologists and biomedical investigators, (2) biophysicists and bioengineers, and (3) biomedical ontologists and informaticists. We present a logical and intuitive semantics of classical physics as a tool for mediating and translating biophysical knowledge among biomedical domains. Daniel L. Cook, MD, PhD John H. Gennari, PhD Maxwell L. Neal, PhD
Author: Mihail Popescu
Publisher: Artech House
ISBN: 1596933712
Category : Medical
Languages : en
Pages : 279
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Book Description
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.
Author: Kenneth Baclawski
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 448
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Book Description
Ontologies as a critical framework for the vast amounts of data in the postgenomic era: an introduction to the basic concepts and applications of ontologies and ontology languages for the life sciences. 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.
Author: Wyatt Travis Clark
Publisher: Springer Science & Business Media
ISBN: 331904138X
Category : Computers
Languages : en
Pages : 46
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Book Description
The development of effective methods for the prediction of ontological annotations is an important goal in computational biology, yet evaluating their performance is difficult due to problems caused by the structure of biomedical ontologies and incomplete annotations of genes. This work proposes an information-theoretic framework to evaluate the performance of computational protein function prediction. A Bayesian network is used, structured according to the underlying ontology, to model the prior probability of a protein's function. The concepts of misinformation and remaining uncertainty are then defined, that can be seen as analogs of precision and recall. Finally, semantic distance is proposed as a single statistic for ranking classification models. The approach is evaluated by analyzing three protein function predictors of gene ontology terms. The work addresses several weaknesses of current metrics, and provides valuable insights into the performance of protein function prediction tools.
Author: Albert Burger
Publisher: Springer Science & Business Media
ISBN: 1846288851
Category : Technology & Engineering
Languages : en
Pages : 354
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Book Description
This book provides a timely and first-of-its-kind collection of papers on anatomy ontologies. It is interdisciplinary in its approach, bringing together the relevant expertise from computing and biomedical studies. The book aims to provide readers with a comprehensive understanding of the foundations of anatomical ontologies and the-state-of-the-art in terms of existing tools and applications. It also highlights challenges that remain today.
Author:
Publisher:
ISBN: 161499854X
Category :
Languages : en
Pages :
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Book Description
