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  • 1.
    Backofen, Rolf
    et al.
    Friedrich-Schiller-Universität Jena, Germany.
    Badea, Liviu
    National Institute for Research and Development in Informatics, Bucharest, Romania.
    Barahona, Pedro
    Universidade Nova de Lisboa, Portugal.
    Berndtsson, Mikael
    University of Skövde, Sweden.
    Burger, Albert
    Heriot-Watt University/MRC Human GeneticsUnit, Edinburgh, UK.
    Dawelbait, Gihan
    Technische Universität Dresden, Germany.
    Doms, Andreas
    Technische Universität Dresden, Germany.
    Fages, Francois
    INRIA Rocquencourt, Paris, France.
    Hotaran, Anca
    National Institute for Research and Development in Informatics, Bucharest, Romania.
    Jakoniené, Vaida
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems.
    Krippahl, Ludwig
    Universidade Nova de Lisboa, Portugal.
    Lambrix, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems.
    McLeod, Kenneth
    Heriot-Watt University/MRC Human GeneticsUnit, Edinburgh, UK.
    Nutt, Werner
    Heriot-Watt University/MRC Human GeneticsUnit, Edinburgh, UK.
    Olsson, Bjorn
    University of Skövde, Sweden.
    Schroeder, Michael
    Technische Universität Dresden, Germany.
    Schroiff, Anna
    University of Skövde, Sweden.
    Royer, Luc
    Technische Universität Dresden, Germany.
    Soliman, Sylvain
    INRIA Rocquencourt, Paris, France.
    Tan, He
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems.
    Tilivea, Doina
    National Institute for Research and Development in Informatics, Bucharest, Romania.
    Will, Sebastian
    Friedrich-Schiller-Universit¨at Jena, Germany.
    Requirements and specification of bioinformatics use cases2005Report (Other academic)
  • 2.
    Backofen, Rolf
    et al.
    Albert-Ludwigs-universität Freiburg, Germany.
    Burger, Albert
    Heriot-Watt university Edinburgh, UK.
    Busch, Anke
    Albert-Ludwigs-universität Freiburg, Germany.
    Dawelbait, Gihan
    TU Dresden, Germany.
    Fages, Francois
    INRIA Rocquencourt Paris, France.
    Jakoniené, Vaida
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    McLeod, Kenneth
    Heriot-Watt university Edinburgh, UK.
    Soliman, Sylvain
    INRIA Rocquencourt Paris, France.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Will, Sebastian
    Albert-Ludwigs-universität Freiburg, Germany.
    Implementation of prototypes2007Report (Other academic)
  • 3.
    Backofen, Rolf
    et al.
    Friedrich-Schiller-Universität Jena, Germany.
    Mike, Badea
    Victoria University of Manchester, UK.
    Barahona, Pedro
    FCT-UNL, Lisbon.
    Burger, Albert
    Harriot-Watt University, Edinburgh, UK.
    Dawelbait, Gihan
    Technical University of Dresden, Germany.
    Doms, Andreas
    Technical University of Dresden, Germany.
    Fages, Francois
    INRIA Rocquencourt, France.
    Hotaran, Anca
    National Institute for Research and Development in Informatics, Romania.
    Jakoniené, Vaida
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems.
    Krippahl, Ludwig
    FCT-UNL, Lisbon.
    Lambrix, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems.
    McLeod, Kenneth
    Harriot-Watt University, Edinburgh, UK.
    Möller, Steffen
    Universität Rostock, Germany.
    Nutt, Werner
    Harriot-Watt University, Edinburgh, UK.
    Olsson, Björn
    University of Skövde, Sweden.
    Schroeder, Michael
    Technical University of Dresden, Germany.
    Soliman, Sylvain
    INRIA Rocquencourt, France.
    Tan, He
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems.
    Tilivea, Doina
    National Institute for Research and Development in Informatics, Romania.
    Will, Sebastian
    Friedrich-Schiller-Universität Jena, Germany.
    Usage of bioinformatics tools and identification of information sources2005Report (Other academic)
  • 4.
    Chen, Bi
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Structure-Based Filtering for Ontology Alignment2006In: Proceedings of the IEEE WETICE Workshop on Semantic Technologies in Collaborative Applications, Institute of Electrical and Electronics Engineers (IEEE), 2006, 364-369 p.Conference paper (Refereed)
    Abstract [en]

    Ontologies are an important technology for the Semantic Web and many ontologies have already been developed. Many ontologies also contain overlapping information and to be able to use them together effectively, we need to align them. Some of the current alignment techniques use information about the structure of the ontologies, but they have not produced good results in evaluations. We propose an approach where, in contrast to the other approaches, structural information is used as a filtering method in the alignment process. We evaluate the approach in terms of quality and performance.

  • 5.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Edberg, Anna
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Manis, Carolyn
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Merging DAML+OIL bio-ontologies2003In: International workshop on description logics, 2003Conference paper (Refereed)
  • 6.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Liu, Qiang
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A system for repairing missing is-a structure in ontologies2009In: Semantic Web Applications and Tools for Life Sciences, 2009Conference paper (Refereed)
  • 7.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Liu, Qiang
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Aligning anatomy ontologies in the Ontology Alignment Evaluation Initiative2009In: 25th Workshop of the Swedish Artificial Intelligence Society, 2009, 13-20 p.Conference paper (Refereed)
  • 8.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Liu, Qiang
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Repairing the missing is-a structure of ontologies2009In: Proceedings of the 4th Asian Semantic Web Conference - ASWC09, Springer Berlin/Heidelberg, 2009, 1, 76-90 p.Chapter in book (Refereed)
    Abstract [en]

    Developing ontologies is not an easy task and often the resultingontologies are not consistent or complete. Such ontologies,although often useful, also lead to problems when used insemantically-enabled applications. Wrong conclusions may bederived or valid conclusions may be missed. To deal with thisproblem we may want to repair the ontologies. Up to date most workhas been performed on finding and repairing the semantic defectssuch as unsatisfiable concepts and inconsistent ontologies. Inthis paper we tackle the problem of repairing modeling defects andin particular, the repairing of structural relations (is-ahierarchy) in the ontologies. We study the case where missing is-arelations are given. We define the notion of a structural repairand develop algorithms to compute repairing actions that wouldallow deriving the missing is-a relations in the repairedontology. Further, we define preferences between repairs. We alsolook at how we can use external knowledge to recommend repairingactions to a domain expert. Further, we discuss an implementedprototype and its use as well as an experiment using theontologies of the Anatomy track of the Ontology AlignmentEvaluation Initiative.

  • 9.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Liu, Qiang
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    RepOSE: an environment for repairing missing ontological structure2009In: The Semantic Web: Fourth Asian Conference, ASWC 2009, Shanghai, China, December 6-9, 2009. Proceedings, Springer Berlin/Heidelberg, 2009, 1, 365-366 p.Chapter in book (Refereed)
    Abstract [en]

    Developing ontologies is not an easy task and often the resultingontologies are not consistent or complete. Such ontologies,although often useful, also lead to problems when used insemantically-enabled applications. Wrong conclusions may bederived or valid conclusions may be missed. To deal with thisproblem we may want to repair the ontologies. Up to date most workhas been performed on finding and repairing the semantic defectssuch as unsatisfiable concepts and inconsistent ontologies. Inthis paper we tackle the problem of repairing modeling defects andin particular, the repairing of structural relations (is-ahierarchy) in the ontologies. We study the case where missing is-arelations are given. We define the notion of a structural repairand develop algorithms to compute repairing actions that wouldallow deriving the missing is-a relations in the repairedontology. Further, we define preferences between repairs. We alsolook at how we can use external knowledge to recommend repairingactions to a domain expert. Further, we discuss an implementedprototype and its use as well as an experiment using theontologies of the Anatomy track of the Ontology AlignmentEvaluation Initiative.

  • 10.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Strömbäck, Lena
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Information integration in bioinformatics with ontologies and standards2009In: Semantic Techniques for the Web: The REWERSE perspective, Springer Berlin/Heidelberg, 2009, 1, 343-376 p.Chapter in book (Refereed)
    Abstract [en]

    New experimental methods allow researchers within molecular and systems biology to rapidly generate larger and larger amounts of data. This data is often made publicly available on the Internet and although this data is extremely useful, we are not using its full capacity. One important reason is that we still lack good ways to connect or integrate information from different resources. One kind of resource is the over 1000 data sources freely available on the Web. As most data sources are developed and maintained independently, they are highly heterogeneous. Information is also updated frequently. Other kinds of resources that are not so well-known or commonly used yet are the ontologies and the standards. Ontologies aim to define a common terminology for a domain of interest. Standards provide a way to exchange data between data sources and tools, even if the internal representations of the data in the resources and tools are different. In this chapter we argue that ontological knowledge and standards should be used for integration of data. We describe properties of the different types of data sources, ontological knowledge and standards that are available on the Web and discuss how this knowledge can be used to support integrated access to multiple biological data sources. Further, we present an integration approach that combines the identified ontological knowledge and standards with traditional information integration techniques. Current integration approaches only cover parts of the suggested approach. We also discuss the components in the model on which much recent work has been done in more detail: ontology-based data source integration, ontology alignment and integration using standards. Although many of our discussions in this chapter are general we exemplify mainly using work done within the REWERSE working group on Adding Semantics to the Bioinformatics Web.

  • 11.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A Framework for Aligning Ontologies2005In: Principles and Practice of Semantic Web Reasoning: Third International Workshop, PPSWR 2005, Dagstuhl Castle, Germany, September 11-16, 2005 Proceedings / [ed] François Fages, Sylvain Soliman, Springer Berlin/Heidelberg, 2005, 17-31 p.Chapter in book (Refereed)
    Abstract [en]

    Ontologies are an important technology for the Semantic Web. In different areas ontologies have already been developed and many of these ontologies contain overlapping information. Often we would therefore want to be able to use multiple ontologies and thus the ontologies need to be aligned. Currently, there exist a number of systems that support users in aligning ontologies, but not many comparative evaluations have been performed. In this paper we present a general framework for aligning ontologies where different alignment strategies can be combined. Further, we exemplify the use of the framework by describing a system (SAMBO) that is developed according to this framework. Within this system we have implemented some already existing alignment algorithms as well as some new algorithms. We also show how the framework can be used to experiment with combinations of strategies. This is a first step towards defining a framework that can be used for comparative evaluations of alignment strategies. For our tests we used several well-known bio-ontologies.

  • 12.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A semi-automatic tool for merging bio-ontologies2004In: Fourth Swedish Bioinformatics Workshop for PhD students and PostDocs, 2004Conference paper (Other academic)
  • 13.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems. Linköping University, The Institute of Technology.
    A semi-automatic tool for merging bio-ontologies2003In: 3rd Swedish annual bioinformatics workshop for PhD students and PostDocs, 2003Conference paper (Other academic)
  • 14.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A Semi-Automatic Tool for Merging Bio-Ontologies2004In: Bioinformatics 2004, 2004, 55-55 p.Conference paper (Other academic)
  • 15.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A Tool for Evaluating Ontology Alignment Strategies2007In: Journal on Data Semantics, ISSN 1861-2032, Vol. VIII, 182-202 p.Article in journal (Refereed)
    Abstract [en]

    Ontologies are an important technology for the Semantic Web. In different areas ontologies have already been developed and many of these ontologies contain overlapping information. Often we would therefore want to be able to use multiple ontologies. To obtain good results, we need to find the relationships between terms in the different ontologies, i.e. we need to align them. Currently, there exist a number of systems that support users in aligning ontologies, but not many comparative evaluations have been performed and there exists little support to perform such evaluations. However, the study of the properties, the evaluation and comparison of the alignment strategies and their combinations, would give us valuable insight in how the strategies could be used in the best way. In this paper we propose the KitAMO framework for comparative evaluation of ontology alignment strategies and their combinations and present our current implementation. We evaluate the implementation with respect to performance. We also illustrate how the system can be used to evaluate and compare alignment strategies and their combinations in terms of performance and quality of the proposed alignments. Further, we show how the results can be analyzed to obtain deeper insights into the properties of the strategies.

  • 16.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Aligning Biomedical Ontologies2007In: Integrative Bioinformatics Workshop,2007, 2007Conference paper (Refereed)
  • 17.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Merging DAML plus OIL Ontologies2005In: Databases and Information Systems: (Selected Papers from the Sixth International Baltic Conference DB&IS'2004) / [ed] Janis Barzdins, Albertas Caplinskas, IOS Press, 2005, 249-258 p.Chapter in book (Refereed)
    Abstract [en]

    Modern databases and information systems essentially differ from their predecessors. Ontology-based and knowledge-based approaches to system development, UML based IS development methodologies, XML databases and heterogeneous information models have come to the fore. All these fundamental aspects are discussed in this book. This publication contains a collection of 22 high quality papers written by 44 authors. These articles present original results in modern database technologies, database applications, data warehousing, data mining, ontologies, and modern information systems. Special emphasis is put on multimedia database systems, heterogeneous data integration methods, view optimizations, ontology engineering tools, modeling and model transformations (MDA). Theoretical aspects as well as technical development issues are considered. The intended audience for this book is researchers, advanced students and practitioners who are interested in advanced topics on databases and information systems

  • 18.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Merging DAML+OIL Ontologies2004In: International Baltic Conference on Databases and Information Systems,2004, 2004, 425- p.Conference paper (Refereed)
  • 19.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Ontology alignment and merging2008In: Anatomy Ontologies for Bioinformatics: Principles and Practice / [ed] Albert Burger, Duncan Davidson, Richard Baldock, Springer Publishing Company, 2008, 133-150 p.Chapter in book (Refereed)
    Abstract [en]

    In recent years many biomedical ontologies, including anatomy ontologies, have been developed. Many of these ontologies contain overlapping information and often we would want to be able to use multiple ontologies. This requires finding the relationships between terms in the different ontologies, i.e. we need to align them. Sometimes we also want to merge ontologies into a new one. In this chapter we give an overview of current ontology alignment and merging systems. We focus on systems that compute similarities between terms in the different ontologies. We present a general framework for these kind of systems and discuss the existing strategies. We also present such a system (SAMBO) and discuss its use using anatomy ontologies. Further, we take a first step in dealing with the problem of using the best alignment algorithms for the ontologies we want to align. We present and illustrate the use of a framework and a tool (KitAMO) for comparative evaluation of ontology alignment strategies and their combinations.

  • 20.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    SAMBO – A System for Aligning and Merging Biomedical Ontologies2006In: Journal of Web Semantics, ISSN 1570-8268, E-ISSN 1873-7749, Vol. 4, no 3, 196-206 p.Article in journal (Refereed)
    Abstract [en]

    Due to the recent explosion of the amount of on-line accessible biomedical data and tools, finding and retrieving the relevant information is not an easy task. The vision of a Semantic Web for life sciences alleviates these difficulties. A key technology for the Semantic Web is ontologies. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. In this paper we propose a framework for aligning and merging ontologies. Further, we developed a system for aligning and merging biomedical ontologies (SAMBO) based on this framework. The framework is also a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations. In this paper we evaluated different strategies and their combinations in terms of quality and processing time and compared SAMBO with two other systems.

  • 21.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Jakoniené, Vaida
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Strömbäck, Lena
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Biological Ontologies2007In: Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences / [ed] Christopher J.O. Baker and Kei-Hoi Cheung, Springer , 2007, 85-99 p.Chapter in book (Refereed)
    Abstract [en]

    Biological ontologies define the basic terms and relations in biological domains and are being used among others, as community reference, as the basis for interoperability between systems, and for search, integration, and exchange of biological data. In this chapter we present examples of biological ontologies and ontology-based knowledge, show how biological ontologies are used and discuss some important issues in ontology engineering.

  • 22.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Liu, Qiang
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    SAMBO and SAMBOdtf results for the Ontology Alignment Evaluation Initiative 20082008In: Third International Workshop on Ontology Matching, 2008, 190-198 p.Conference paper (Refereed)
  • 23.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Xu, Wei
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Literature-based alignment of ontologies.2008In: Third International Workshop on Ontology Matching, 2008, 219-223 p.Conference paper (Refereed)
  • 24.
    Strömbäck, Lena
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Jakoniené, Vaida
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Representing, storing and accessing molecular interaction data: a review of models and tools2006In: Briefings in Bioinformatics, ISSN 1467-5463, E-ISSN 1477-4054, Vol. 7, no 4, 331-338 p.Article in journal (Refereed)
    Abstract [en]

    One important aim within systems biology is to integrate disparate pieces of information, leading to discovery of higher-level knowledge about important functionality within living organisms. This makes standards for representation of data and technology for exchange and integration of data important key points for development within the area. In this article, we focus on the recent developments within the field. We compare the recent updates to the three standard representations for exchange of data SBML, PSI MI and BioPAX. In addition, we give an overview of available tools for these three standards and a discussion on how these developments support possibilities for data exchange and integration.

  • 25.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A study on the relation between linguistics-oriented and domain-specific semantics2010In: Proceedings of the 3rd International Workshop on Semantic Web Applications and Tools for the Life Sciences, 2010Conference paper (Refereed)
    Abstract [en]

    In this paper we dealt with the comparison and linking between lexical resources with domain knowledge provided by ontologies. It is one of the issues for the combination of the Semantic Web Ontologies and Text Mining. We investigated the relations between the linguisticsoriented and domain-specific semantics, by associating the GO biological process concepts to the FrameNet semantic frames. The result shows the gaps between the linguistics-oriented and domain-specific semantics on the classification of events and the grouping of target words. The result provides valuable information for the improvement of domain ontologies supporting for text mining systems. And also, it will result in benefits to language understanding technology.

  • 26.
    Tan, He
    Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems. Linköping University, The Institute of Technology.
    Aligning and Merging Biomedical Ontologies2006Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Due to the explosion of the amount of biomedical data, knowledge and tools that are often publicly available over the Web, a number of difficulties are experienced by biomedical researchers. For instance, it is difficult to find, retrieve and integrate information that is relevant to their research tasks. Ontologies and the vision of a Semantic Web for life sciences alleviate these difficulties. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. A number of systems have been developed for aligning and merging ontologies and various alignment strategies are used in these systems. However, there are no general methods to support building such tools, and there exist very few evaluations of these strategies. In this thesis we give an overview of the existing systems. We propose a general framework for aligning and merging ontologies. Most existing systems can be seen as instantiations of this framework. Further, we develop SAMBO (System for Aligning and Merging Biomedical Ontologies) according to this framework. We implement different alignment strategies and their combinations, and evaluate them in terms of quality and processing time within SAMBO. We also compare SAMBO with two other systems. The work in this thesis is a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations.

    List of papers
    1. SAMBO – A System for Aligning and Merging Biomedical Ontologies
    Open this publication in new window or tab >>SAMBO – A System for Aligning and Merging Biomedical Ontologies
    2006 (English)In: Journal of Web Semantics, ISSN 1570-8268, E-ISSN 1873-7749, Vol. 4, no 3, 196-206 p.Article in journal (Refereed) Published
    Abstract [en]

    Due to the recent explosion of the amount of on-line accessible biomedical data and tools, finding and retrieving the relevant information is not an easy task. The vision of a Semantic Web for life sciences alleviates these difficulties. A key technology for the Semantic Web is ontologies. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. In this paper we propose a framework for aligning and merging ontologies. Further, we developed a system for aligning and merging biomedical ontologies (SAMBO) based on this framework. The framework is also a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations. In this paper we evaluated different strategies and their combinations in terms of quality and processing time and compared SAMBO with two other systems.

    Place, publisher, year, edition, pages
    Elsevier, 2006
    Keyword
    Ontologies; Alignment; Merging; Biomedical informatics
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-14575 (URN)10.1016/j.websem.2006.05.003 (DOI)000247054000005 ()
    Available from: 2007-07-03 Created: 2007-07-03 Last updated: 2017-12-13Bibliographically approved
    2. Alignment of Biomedical Ontologies using Life Science Literature
    Open this publication in new window or tab >>Alignment of Biomedical Ontologies using Life Science Literature
    Show others...
    2006 (English)In: Proceedings of the International Workshop on Knowledge Discovery in Life Science Literature / [ed] Eric G. Bremer, Springer Berlin/Heidelberg, 2006, 1-17 p.Chapter in book (Refereed)
    Abstract [en]

    This book constitutes the refereed proceedings of the International Workshop on Knowledge Discovery in Life Science Literature, KDLL 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006).

    The 12 revised full papers presented together with two invited talks were carefully reviewed and selected for inclusion in the book. The papers cover all topics of knowledge discovery in life science data such as text mining, identification and retrieval of documents, passage retrieval, co-reference resolution, extraction of life science entities or relationships from large collections, automated characterization of biological, biomedical and biotechnological entities and processes, extraction and characterization of more complex patterns and interaction networks, automated generation of text summaries, automated construction, expansion and curation of ontologies for different domains, and construction of controlled vocabularies.

    Place, publisher, year, edition, pages
    Springer Berlin/Heidelberg, 2006
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 3886
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-14035 (URN)10.1007/11683568_1 (DOI)000237198800001 ()978-3-540-32809-4 (ISBN)3-540-32809-2 (ISBN)
    Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2018-01-13Bibliographically approved
  • 27.
    Tan, He
    Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems. Linköping University, The Institute of Technology.
    Aligning Biomedical Ontologies2007Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The amount of biomedical information that is disseminated over the Web increases every day. This rich resource is used to find solutions to challenges across the life sciences. The Semantic Web for life sciences shows promise for effectively and efficiently locating, integrating, querying and inferring related information that is needed in daily biomedical research. One of the key technologies in the Semantic Web is ontologies, which furnish the semantics of the Semantic Web. A large number of biomedical ontologies have been developed. Many of these ontologies contain overlapping information, but it is unlikely that eventually there will be one single set of standard ontologies to which everyone will conform. Therefore, applications often need to deal with multiple overlapping ontologies, but the heterogeneity of ontologies hampers interoperability between different ontologies. Aligning ontologies, i.e. identifying relationships between different ontologies, aims to overcome this problem. A number of ontology alignment systems have been developed. In these systems various techniques and ideas have been proposed to facilitate identification of alignments between ontologies. However, there still is a range of issues to be addressed when we have alignment problems at hand. The work in this thesis contributes to three different aspects of identification of high quality alignments: 1) Ontology alignment strategies and systems. We surveyed the existing ontology alignment systems, and proposed a general ontology alignment framework. Most existing systems can be seen as instantiations of the framework. Also, we developed a system for aligning biomedical ontologies (SAMBO) according to this framework. We implemented various alignment strategies in the system. 2) Evaluation of ontology alignment strategies. We developed and implemented the KitAMO framework for comparative evaluation of different alignment strategies, and we evaluated different alignment strategies using the implementation. 3) Recommending optimal alignment strategies for different applications. We proposed a method for making recommendations.

    List of papers
    1. SAMBO – A System for Aligning and Merging Biomedical Ontologies
    Open this publication in new window or tab >>SAMBO – A System for Aligning and Merging Biomedical Ontologies
    2006 (English)In: Journal of Web Semantics, ISSN 1570-8268, E-ISSN 1873-7749, Vol. 4, no 3, 196-206 p.Article in journal (Refereed) Published
    Abstract [en]

    Due to the recent explosion of the amount of on-line accessible biomedical data and tools, finding and retrieving the relevant information is not an easy task. The vision of a Semantic Web for life sciences alleviates these difficulties. A key technology for the Semantic Web is ontologies. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. In this paper we propose a framework for aligning and merging ontologies. Further, we developed a system for aligning and merging biomedical ontologies (SAMBO) based on this framework. The framework is also a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations. In this paper we evaluated different strategies and their combinations in terms of quality and processing time and compared SAMBO with two other systems.

    Place, publisher, year, edition, pages
    Elsevier, 2006
    Keyword
    Ontologies; Alignment; Merging; Biomedical informatics
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-14575 (URN)10.1016/j.websem.2006.05.003 (DOI)000247054000005 ()
    Available from: 2007-07-03 Created: 2007-07-03 Last updated: 2017-12-13Bibliographically approved
    2. Alignment of Biomedical Ontologies using Life Science Literature
    Open this publication in new window or tab >>Alignment of Biomedical Ontologies using Life Science Literature
    Show others...
    2006 (English)In: Proceedings of the International Workshop on Knowledge Discovery in Life Science Literature / [ed] Eric G. Bremer, Springer Berlin/Heidelberg, 2006, 1-17 p.Chapter in book (Refereed)
    Abstract [en]

    This book constitutes the refereed proceedings of the International Workshop on Knowledge Discovery in Life Science Literature, KDLL 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006).

    The 12 revised full papers presented together with two invited talks were carefully reviewed and selected for inclusion in the book. The papers cover all topics of knowledge discovery in life science data such as text mining, identification and retrieval of documents, passage retrieval, co-reference resolution, extraction of life science entities or relationships from large collections, automated characterization of biological, biomedical and biotechnological entities and processes, extraction and characterization of more complex patterns and interaction networks, automated generation of text summaries, automated construction, expansion and curation of ontologies for different domains, and construction of controlled vocabularies.

    Place, publisher, year, edition, pages
    Springer Berlin/Heidelberg, 2006
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 3886
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-14035 (URN)10.1007/11683568_1 (DOI)000237198800001 ()978-3-540-32809-4 (ISBN)3-540-32809-2 (ISBN)
    Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2018-01-13Bibliographically approved
    3. Structure-Based Filtering for Ontology Alignment
    Open this publication in new window or tab >>Structure-Based Filtering for Ontology Alignment
    2006 (English)In: Proceedings of the IEEE WETICE Workshop on Semantic Technologies in Collaborative Applications, Institute of Electrical and Electronics Engineers (IEEE), 2006, 364-369 p.Conference paper, Published paper (Refereed)
    Abstract [en]

    Ontologies are an important technology for the Semantic Web and many ontologies have already been developed. Many ontologies also contain overlapping information and to be able to use them together effectively, we need to align them. Some of the current alignment techniques use information about the structure of the ontologies, but they have not produced good results in evaluations. We propose an approach where, in contrast to the other approaches, structural information is used as a filtering method in the alignment process. We evaluate the approach in terms of quality and performance.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2006
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-14577 (URN)10.1109/WETICE.2006.64 (DOI)000245542500064 ()9780769526232 (ISBN)
    Conference
    IEEE WETICE Workshop on Semantic Technologies in Collaborative Applications
    Available from: 2007-07-03 Created: 2007-07-03 Last updated: 2016-12-06
    4. A Tool for Evaluating Ontology Alignment Strategies
    Open this publication in new window or tab >>A Tool for Evaluating Ontology Alignment Strategies
    2007 (English)In: Journal on Data Semantics, ISSN 1861-2032, Vol. VIII, 182-202 p.Article in journal (Refereed) Published
    Abstract [en]

    Ontologies are an important technology for the Semantic Web. In different areas ontologies have already been developed and many of these ontologies contain overlapping information. Often we would therefore want to be able to use multiple ontologies. To obtain good results, we need to find the relationships between terms in the different ontologies, i.e. we need to align them. Currently, there exist a number of systems that support users in aligning ontologies, but not many comparative evaluations have been performed and there exists little support to perform such evaluations. However, the study of the properties, the evaluation and comparison of the alignment strategies and their combinations, would give us valuable insight in how the strategies could be used in the best way. In this paper we propose the KitAMO framework for comparative evaluation of ontology alignment strategies and their combinations and present our current implementation. We evaluate the implementation with respect to performance. We also illustrate how the system can be used to evaluate and compare alignment strategies and their combinations in terms of performance and quality of the proposed alignments. Further, we show how the results can be analyzed to obtain deeper insights into the properties of the strategies.

    Place, publisher, year, edition, pages
    Springer Berlin/Heidelberg, 2007
    Keyword
    ontologies, alignment, evaluation
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-14578 (URN)10.1007/978-3-540-70664-9_7 (DOI)978-3-540-70663-2 (ISBN)
    Available from: 2007-07-03 Created: 2007-07-03 Last updated: 2018-01-13
    5. A Method for Recommending Ontology Alignment Strategies
    Open this publication in new window or tab >>A Method for Recommending Ontology Alignment Strategies
    2007 (English)In: Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference - ISWC / ASWC 07 / [ed] International Semantic Web Conference, Springer Berlin/Heidelberg, 2007, 494-507 p.Chapter in book (Refereed)
    Abstract [en]

    In different areas ontologies have been developed and many of these ontologies contain overlapping information. Often we would therefore want to be able to use multiple ontologies. To obtain good results, we need to find the relationships between terms in the different ontologies, i.e. we need to align them. Currently, there already exist a number of different alignment strategies. However, it is usually difficult for a user that needs to align two ontologies to decide which of the different available strategies are the most suitable. In this paper we propose a method that provides recommendations on alignment strategies for a given alignment problem. The method is based on the evaluation of the different available alignment strategies on several small selected pieces from the ontologies, and uses the evaluation results to provide recommendations. In the paper we give the basic steps of the method, and then illustrate and discuss the method in the setting of an alignment problem with two well-known biomedical ontologies. We also experiment with different implementations of the steps in the method.

    Place, publisher, year, edition, pages
    Springer Berlin/Heidelberg, 2007
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 4825
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-14579 (URN)10.1007/978-3-540-76298-0_36 (DOI)000251080500036 ()978-3-540-76297-3 (ISBN)
    Conference
    ISWC 2007
    Note

    The book is based on the proceedings presented at the 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, Busan, Korea, November 11-15, 2007.

    Available from: 2007-07-03 Created: 2007-07-03 Last updated: 2018-01-13Bibliographically approved
  • 28.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Knowledge-based Gene Symbol Disambiguation2008In: Second International Workshop on Data and Text Mining in Bioinformatics,2008, New York: ACM , 2008, 73-76 p.Conference paper (Refereed)
    Abstract [en]

    Since there is no standard naming convention for genes and gene products, gene symbol disambiguation (GSD) has become a big challenge when mining biomedical literature. Several GSD methods have been proposed based on Medline references to genes. However, nowadays gene databases, e.g. Entrez Gene, provide plenty of information about genes, and many biomedical ontologies, e.g. UMLS Metathesaurus and Semantic Network, have been developed. These knowledge sources could be used for disambiguation, in this paper we propose a method which relies on information about gene candidates from gene databases, contexts of gene symbols and biomedical ontologies. We implement our method, and evaluate the performance of the implementation using BioCreAtIvE II data sets.

  • 29.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Jakoniené, Vaida
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Åberg, Johan
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Shahmehri, Nahid
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Alignment of Biomedical Ontologies using Life Science Literature2006In: Proceedings of the International Workshop on Knowledge Discovery in Life Science Literature / [ed] Eric G. Bremer, Springer Berlin/Heidelberg, 2006, 1-17 p.Chapter in book (Refereed)
    Abstract [en]

    This book constitutes the refereed proceedings of the International Workshop on Knowledge Discovery in Life Science Literature, KDLL 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006).

    The 12 revised full papers presented together with two invited talks were carefully reviewed and selected for inclusion in the book. The papers cover all topics of knowledge discovery in life science data such as text mining, identification and retrieval of documents, passage retrieval, co-reference resolution, extraction of life science entities or relationships from large collections, automated characterization of biological, biomedical and biotechnological entities and processes, extraction and characterization of more complex patterns and interaction networks, automated generation of text summaries, automated construction, expansion and curation of ontologies for different domains, and construction of controlled vocabularies.

  • 30.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Kaliyaperumal, Rajaram
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Benis, Nirupama
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Building frame-based corpus on the basis of ontological domain knowledge2011In: Proceedings of the Workshop on BioNLP, Association for Computational Linguistics, 2011, 74-82 p.Conference paper (Refereed)
    Abstract [en]

    Semantic Role Labeling (SRL) plays a key role in many NLP applications. The development of SRL systems for the biomedical domain is frustrated by the lack of large domain-specific corpora that are labeled with semantic roles. Corpus development has been very expensive and time-consuming. In this paper we propose a method for building frame-based corpus on the basis of domain knowledge provided by ontologies. We believe that ontologies, as a structured and semantic representation of domain knowledge, can instruct and ease the tasks in building the corpora. In the paper we present a corpus built by using the method. We compared it to BioFrameNet, and examined the gaps between the semantic classification of the target words in the domain-specific corpus and in FrameNet and Prop-Bank/VerbNet.

  • 31.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Kaliyaperumal, Rajaram
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Benis, Nirupama
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Ontology-driven Construction of Corpus with Frame Semantics Annotations2011In: poster at The Fourth International Symposium on Languages in Biology and Medicine, 2011Conference paper (Refereed)
  • 32.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Kaliyaperumal, Rajaram
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Benis, Nirupama
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Ontology-Driven Construction of Domain Corpus with Frame Semantics Annotations2012In: Computational linguistics and intelligent text processing, Springer Berlin/Heidelberg, 2012, 54-65 p.Conference paper (Refereed)
    Abstract [en]

    Semantic Role Labeling plays a key role in many text mining applications. The development of SRL systems for the biomedical domain is frustrated by the lack of large domain specific corpora that are labeled with semantic roles. In this paper we proposed a method for building corpus that are labeled with semantic roles for the domain of biomedicine. The method is based on the theory of frame semantics, and uses domain knowledge provided by ontologies. By using the method, we have built a corpus for transport events strictly following the domain knowledge provided by GO biological process ontology. We compared one of our frames to a BioFrameNet frame. We also examined the gaps between the semantic classification of the target words in this domain-specific corpus and in FrameNet and PropBank/VerbNet data. The successful corpus construction demonstrates that ontologies, as a formal representation of domain knowledge, can instruct us and ease all the tasks in building this kind of corpus. Furthermore, ontological domain knowledge leads to well-defined semantics exposed on the corpus, which will be very valuable in text mining applications.

  • 33.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A Method for Recommending Ontology Alignment Strategies2007In: Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference - ISWC / ASWC 07 / [ed] International Semantic Web Conference, Springer Berlin/Heidelberg, 2007, 494-507 p.Chapter in book (Refereed)
    Abstract [en]

    In different areas ontologies have been developed and many of these ontologies contain overlapping information. Often we would therefore want to be able to use multiple ontologies. To obtain good results, we need to find the relationships between terms in the different ontologies, i.e. we need to align them. Currently, there already exist a number of different alignment strategies. However, it is usually difficult for a user that needs to align two ontologies to decide which of the different available strategies are the most suitable. In this paper we propose a method that provides recommendations on alignment strategies for a given alignment problem. The method is based on the evaluation of the different available alignment strategies on several small selected pieces from the ontologies, and uses the evaluation results to provide recommendations. In the paper we give the basic steps of the method, and then illustrate and discuss the method in the setting of an alignment problem with two well-known biomedical ontologies. We also experiment with different implementations of the steps in the method.

  • 34.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Aligning and merging biomedical ontologies2006In: Seventh Swedish Bioinformatics Workshop for PhD students and PostDocs,2006, 2006, 18-18 p.Conference paper (Other academic)
  • 35.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    SAMBO results for the Ontology Alignment Evaluation Initiative 20072007In: International Workshop on Ontology Matching,2007, CEURWS , 2007, 236- p.Conference paper (Refereed)
    Abstract [en]

    This article describes a system for ontology alignment, SAMBO, and presents its results for the benchmark and anatomy tasks in the 2007 Ontology Alignment Evaluation Initiative. For the benchmark task we have used a strategy based on string matching as well as the use of a thesaurus, and obtained good results in many cases. For the anatomy task we have used a combination of string matching and the use of domain knowledge. This combination performed well in former evaluations using other anatomy ontologies.

  • 36.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Selecting an ontology for biomedical text mining2009In: 17th Conference on Intelligent Systems for Molecular Biology, 2009Conference paper (Refereed)
  • 37.
    Tan, He
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Selecting an ontology for biomedical text mining2009In: Workshop on BioNLP, 2009, 55-62 p.Conference paper (Refereed)
  • 38.
    Wächter, Thomas
    et al.
    Biotechnologisches Zentrum, TU Dresden, Germany.
    Tan, He
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Wobst, André
    Biotechnologisches Zentrum, TU Dresden, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Schroeder, Michael
    Biotechnologisches Zentrum, TU Dresden, Germany.
    A Corpus-driven Approach for Design, Evolution and Alignment of Ontologies2006In: Winter Simulation Conference,2006, 2006, 1595- p.Conference paper (Refereed)
    Abstract [en]

    Bio-ontologies are hierarchical vocabularies, which are used to annotate other data sources such as sequence and structure databases. With the wide use of ontologies their integration, design, and evolution becomes an important problem. We show how textmining on relevant text corpora can be used to identify matching ontology terms of two separate ontologies and to propose new ontology terms for a given term. We evaluate these approaches on the GeneOntology.

1 - 38 of 38
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