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Jakoniené, Vaida
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Publications (10 of 19) Show all publications
Lambrix, P., Tan, H., Jakoniené, V. & Strömbäck, L. (2007). Biological Ontologies. In: Christopher J.O. Baker and Kei-Hoi Cheung (Ed.), Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences: (pp. 85-99). Springer
Open this publication in new window or tab >>Biological Ontologies
2007 (English)In: Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences / [ed] Christopher J.O. Baker and Kei-Hoi Cheung, Springer , 2007, p. 85-99Chapter 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.

Place, publisher, year, edition, pages
Springer, 2007
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-35076 (URN)10.1007/978-0-387-48438-9_5 (DOI)24811 (Local ID)0-387-48436-1 (ISBN)978-0-387-48436-5 (ISBN)24811 (Archive number)24811 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2018-01-13Bibliographically approved
Backofen, R., Burger, A., Busch, A., Dawelbait, G., Fages, F., Jakoniené, V., . . . Will, S. (2007). Implementation of prototypes. REWERSE: REWERSE
Open this publication in new window or tab >>Implementation of prototypes
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2007 (English)Report (Other academic)
Place, publisher, year, edition, pages
REWERSE: REWERSE, 2007
Series
REWERSE ; A2-D6
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-37720 (URN)- (ISRN)37865 (Local ID)37865 (Archive number)37865 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2018-01-13
Jakoniené, V. & Lambrix, P. (2007). Tool for Evaluating Strategies for Grouping of Biological Data. Journal of Integrative Bioinformatics, 4(3)
Open this publication in new window or tab >>Tool for Evaluating Strategies for Grouping of Biological Data
2007 (English)In: Journal of Integrative Bioinformatics, ISSN 1613-4516, Vol. 4, no 3Article in journal (Refereed) Published
Abstract [en]

During the last decade an enormous amount of biological data has been generated and techniques and tools to analyze this data have been developed. Many of these tools use some form of grouping and are used in, for instance, data integration, data cleaning, prediction of protein functionality, and correlation of genes based on microarray data. A number of aspects influence the quality of the grouping results: the data sources, the grouping attributes and the algorithms implementing the grouping procedure. Many methods exist, but it is often not clear which methods perform best for which grouping tasks. The study of the properties, and the evaluation and the comparison of the different aspects that influence the quality of the grouping results, would give us valuable insight in how the grouping procedures could be used in the best way. It would also lead to recommendations on how to improve the current procedures and develop new procedures. To be able to perform such studies and evaluations we need environments that allow us to compare and evaluate different grouping strategies. In this paper we present a framework, KitEGA, for such an environment, and present its current prototype implementation. We illustrate its use by comparing grouping strategies for classifying proteins regarding biological function and isozymes.

National Category
Engineering and Technology Computer Sciences Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:liu:diva-14037 (URN)10.2390/biecoll-jib-2007-83 (DOI)
Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2018-01-13
Jakoniené, V., Rundqvist, D. & Lambrix, P. (2006). A Method for Similarity-Based Grouping of Biological Data. In: Ulf Leser, Felix Naumann, Barbara Eckman (Ed.), Ulf Leser, Felix Naumann, Barbara Eckman (Ed.), 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: . Paper presented at 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. (pp. 136-151). Springer Berlin/Heidelberg
Open this publication in new window or tab >>A Method for Similarity-Based Grouping of Biological Data
2006 (English)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 / [ed] Ulf Leser, Felix Naumann, Barbara Eckman, Springer Berlin/Heidelberg, 2006, p. 136-151Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2006
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 4075
Series
Lecture Notes in Bioinformatics ; 4075
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-14036 (URN)10.1007/11799511_13 (DOI)000239622300011 ()978-3-540-36595-2 (ISBN)978-3-540-36593-8 (ISBN)
Conference
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.
Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2018-11-27Bibliographically approved
Jakoniené, V. & Lambrix, P. (2006). A tool for evaluating strategies for grouping of biological data. In: Seventh Swedish Bioinformatics Workshop for PhD students and PostDocs,2006: . Paper presented at Seventh Swedish Bioinformatics Workshop for PhD students and PostDocs,2006 (pp. 23-24).
Open this publication in new window or tab >>A tool for evaluating strategies for grouping of biological data
2006 (English)In: Seventh Swedish Bioinformatics Workshop for PhD students and PostDocs,2006, 2006, p. 23-24Conference paper, Published paper (Other academic)
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-35715 (URN)28266 (Local ID)28266 (Archive number)28266 (OAI)
Conference
Seventh Swedish Bioinformatics Workshop for PhD students and PostDocs,2006
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2018-01-13
Tan, H., Jakoniené, V., Lambrix, P., Åberg, J. & Shahmehri, N. (2006). Alignment of Biomedical Ontologies using Life Science Literature. In: Eric G. Bremer (Ed.), Eric G. Bremer, Jörg Hakenberg, Eui-Hong (Sam) Han, Daniel Berrar and Werner Dubitzky (Ed.), KDLL: International Workshop on Knowledge Discovery in Life Science LIterature Knowledge Discovery in Life Science Literature PAKDD 2006 International Workshop, KDLL 2006, Singapore, April 9, 2006. Proceedings: . Paper presented at KDLL: International Workshop on Knowledge Discovery in Life Science LIterature Knowledge Discovery in Life Science Literature PAKDD 2006 International Workshop, KDLL 2006, Singapore, April 9, 2006 (pp. 1-17). Berlin/Heidelberg: Springer
Open this publication in new window or tab >>Alignment of Biomedical Ontologies using Life Science Literature
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2006 (English)In: KDLL: International Workshop on Knowledge Discovery in Life Science LIterature Knowledge Discovery in Life Science Literature PAKDD 2006 International Workshop, KDLL 2006, Singapore, April 9, 2006. Proceedings / [ed] Eric G. Bremer, Jörg Hakenberg, Eui-Hong (Sam) Han, Daniel Berrar and Werner Dubitzky, Berlin/Heidelberg: Springer, 2006, p. 1-17Conference paper, Published paper (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
Berlin/Heidelberg: Springer, 2006
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 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)
Conference
KDLL: International Workshop on Knowledge Discovery in Life Science LIterature Knowledge Discovery in Life Science Literature PAKDD 2006 International Workshop, KDLL 2006, Singapore, April 9, 2006
Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2018-11-27Bibliographically approved
Jakoniené, V. & Lambrix, P. (2006). Information integration systems for biological data source requirements and opportunities.
Open this publication in new window or tab >>Information integration systems for biological data source requirements and opportunities
2006 (English)Report (Other (popular science, discussion, etc.))
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-14033 (URN)
Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2018-01-13
Jakonienė, V. (2006). Integration of Biological Data. (Doctoral dissertation). Institutionen för datavetenskap
Open this publication in new window or tab >>Integration of Biological Data
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Data integration is an important procedure underlying many research tasks in the life sciences, as often multiple data sources have to be accessed to collect the relevant data. The data sources vary in content, data format, and access methods, which often vastly complicates the data retrieval process. As a result, the task of retrieving data requires a great deal of effort and expertise on the part of the user. To alleviate these difficulties, various information integration systems have been proposed in the area. However, a number of issues remain unsolved and new integration solutions are needed.

The work presented in this thesis considers data integration at three different levels. 1) Integration of biological data sources deals with integrating multiple data sources from an information integration system point of view. We study properties of biological data sources and existing integration systems. Based on the study, we formulate requirements for systems integrating biological data sources. Then, we define a query language that supports queries commonly used by biologists. Also, we propose a high-level architecture for an information integration system that meets a selected set of requirements and that supports the specified query language. 2) Integration of ontologies deals with finding overlapping information between ontologies. We develop and evaluate algorithms that use life science literature and take the structure of the ontologies into account. 3) Grouping of biological data entries deals with organizing data entries into groups based on the computation of similarity values between the data entries. We propose a method that covers the main steps and components involved in similarity-based grouping procedures. The applicability of the method is illustrated by a number of test cases. Further, we develop an environment that supports comparison and evaluation of different grouping strategies.

The work is supported by the implementation of: 1) a prototype for a system integrating biological data sources, called BioTRIFU, 2) algorithms for ontology alignment, and 3) an environment for evaluating strategies for similarity-based grouping of biological data, called KitEGA.

Place, publisher, year, edition, pages
Institutionen för datavetenskap, 2006. p. 20
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1035
Keywords
Datalogi, integration, grouping, databases, ontologies, biological data, ioinformatics, KitEGA, Datalogi
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-7484 (URN)91-85523-28-3 (ISBN)
Public defence
2006-09-25, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2017-08-15Bibliographically approved
Doms, A., Jakoniené, V., Lambrix, P., Schroeder, M. & Wächter, T. (2006). Ontologies and Text Mining as a Basis for a Semantic Web for the Life Sciences. In: Pedro BarahonaFrançois Bry, Enrico Franconi, Nicola Henze et (Ed.), Reasoning Web, Second International Summer School: Summer School 2006, Lisbon, Portugal, September 4-8, 2006, Tutorial Lectures (pp. 164-183). Springer Berlin/Heidelberg
Open this publication in new window or tab >>Ontologies and Text Mining as a Basis for a Semantic Web for the Life Sciences
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2006 (English)In: Reasoning Web, Second International Summer School: Summer School 2006, Lisbon, Portugal, September 4-8, 2006, Tutorial Lectures / [ed] Pedro BarahonaFrançois Bry, Enrico Franconi, Nicola Henze et, Springer Berlin/Heidelberg, 2006, p. 164-183Chapter in book (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2006
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 4126
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-34038 (URN)10.1007/11837787_7 (DOI)000240539300007 ()20533 (Local ID)978-3-5403-8409-0 (ISBN)20533 (Archive number)20533 (OAI)
Note

LNCS 4126 3-540-38-409-X

Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2019-04-02Bibliographically approved
Strömbäck, L., Jakoniené, V., Tan, H. & Lambrix, P. (2006). Representing, storing and accessing molecular interaction data: a review of models and tools. Briefings in Bioinformatics, 7(4), 331-338
Open this publication in new window or tab >>Representing, storing and accessing molecular interaction data: a review of models and tools
2006 (English)In: Briefings in Bioinformatics, ISSN 1467-5463, E-ISSN 1477-4054, Vol. 7, no 4, p. 331-338Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Oxford University Press, 2006
Keywords
molecular interactions, cellular pathways, standardization, SBML, PSI MI, BioPAX
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-35521 (URN)10.1093/bib/bbl039 (DOI)000242471000003 ()17132622 (PubMedID)27369 (Local ID)27369 (Archive number)27369 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2018-01-13Bibliographically approved
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