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| 2. |
- Backofen, Rolf, et al.
(author)
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Requirements and specification of bioinformatics use cases
- 2005
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Reports (other academic/artistic)abstract
- This deliverable specifies use cases based on bioinformatics research carried out by members ofA2. The use cases involve the use of rules to reason over ontologies and pathways (Dresden,Edinburgh, Paris, Linköping) and rules to specify workflows to integrate bioinformatics data (Lisbon, Skövde, Jena, Bucharest). The use cases are designed as a reference point to foster the take up of A2 use cases by I-work packages. Most notably, many of the use cases specify the need for querying and reactivity with languages like Xcerpt (I4), Erus (I5) and Prova (I5). The use cases range from basic research applications to fully deployed software with an international user base.
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| 3. |
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| 4. |
- Backofen, Rolf, et al.
(author)
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Usage of bioinformatics tools and identification of information sources
- 2005
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Reports (other academic/artistic)abstract
- Bioinformatics is an important application area for semantic web technologies as much of the data is online and accessible in XML format, as some sites already support web services, and as ontologies are widely used to annotate data. In this deliverable, we give a survey over 18 of the most important bioinformatics resources and discuss their availability and accessibility, which are two of the main criteria for these resources to act as bases for later demonstrators.
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| 6. |
- Doms, Andreas, et al.
(author)
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Ontologies and Text Mining as a Basis for a Semantic Web for the Life Sciences
- 2006
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In: Reasoning Web, Second International Summer School. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540384090 ; , s. 164-183
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Book chapter (peer-reviewed)abstract
- This book presents thoroughly arranged tutorial papers corresponding to lectures given by leading researchers at the Second International Summer School on Reasoning Web in Lisbon, Portugal, in September 2006. Building on the predessor school held in 2005 and published as LNCS 3564, the ten tutorial lectures presented provide competent coverage of current topics in semantic Web research and development.
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| 7. |
- Jakoniené, Vaida, et al.
(author)
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A Method for Similarity-Based Grouping of Biological Data
- 2006
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In: DILS: International Workshop on Data Integration in the Life Sciences Data Integration in the Life Sciences Third International Workshop, DILS 2006, Hinxton, UK, July 20-22, 2006. Proceedings. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540365952 - 9783540365938 ; , s. 136-151
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Conference paper (peer-reviewed)abstract
- Similarity-based grouping of data entries in one or more data sources is a task underlying many different data management tasks, such as, structuring search results, removal of redundancy in databases and data integration. Similarity-based grouping of data entries is not a trivial task in the context of life science data sources as the stored data is complex, highly correlated and represented at different levels of granularity. The contribution of this paper is two-fold. 1) We propose a method for similarity-based grouping and 2) we show results from test cases. As the main steps the method contains specification of grouping rules, pairwise grouping between entries, actual grouping of similar entries, and evaluation and analysis of the results. Often, different strategies can be used in the different steps. The method enables exploration of the influence of the choices and supports evaluation of the results with respect to given classifications. The grouping method is illustrated by test cases based on different strategies and classifications. The results show the complexity of the similarity-based grouping tasks and give deeper insights in the selected grouping tasks, the analyzed data source, and the influence of different strategies on the results.
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| 8. |
- Jakoniené, Vaida, 1974-
(author)
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A study in integrating multiple biological data sources
- 2005
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Licentiate thesis (other academic/artistic)abstract
- Life scientists often have to retrieve data from multiple biological data sources to solve their research problems. Although many data sources are available, they vary in content, data format, and access methods, which often vastly complicates the data retrieval process. The user must decide which data sources to access and in which order, how to retrieve the data and how to combine the results - in short, the task of retrieving data requires a great deal of effort and expertise on the part of the user.Information integration systems aim to alleviate these problems by providing a uniform (or even integrated) interface to biological data sources. The information integration systems currently available for biological data sources use traditional integration approaches. However, biological data and data sources have unique properties which introduce new challenges, requiring development of new solutions and approaches.This thesis is part of the BioTrifu project, which explores approaches to integrating multiple biological data sources. First, the thesis describes properties of biological data sources and existing systems that enable integrated access to them. Based on the study, requirements for systems integrating biological data sources are formulated and the challenges involved in developing such systems are discussed. Then, the thesis presents a query language and a high-level architecture for the BioTrifu system that meet these requirements. An approach to generating a query plan in the presence of alternative data sources and ways to integrate the data is then developed. Finally, the design and implementation of a prototype for the BioTrifu system are presented.
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