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Erlendsson, Björn
Publications (9 of 9) Show all publications
Gawronska, B., Nikolayenkova, O. & Erlendsson, B. (2006). A corpus based analysis of English, Swedish, Polish, and Russian prepositions. In: ISCA Tutorial and Research Workshop on Experimental Linguistics (pp. 137-140).
Open this publication in new window or tab >>A corpus based analysis of English, Swedish, Polish, and Russian prepositions
2006 (English)In: ISCA Tutorial and Research Workshop on Experimental Linguistics, 2006, p. 137-140Conference paper, Published paper (Other academic)
Abstract [en]

In this study, the use of most frequent spatial prepositions in English, Polish, Swedish, and Russian is analyzed. The prepositions and their contexts are extracted from corpora by means of concordance tools. The collostructional strength between the prepositions and the most frequent nouns in the PPs (Gries et al. 2005) is then computed in order to get a more detailed picture of the contexts in which a given preposition is most likely to appear. The results of the investigation are then analysed within the framework of cognitive semantics, especially Croft and Cruse's (2004) taxonomy of construal operations, and Talmy’s (2005) classification of spatial images

Identifiers
urn:nbn:se:his:diva-1918 (URN)960-6608-57-3 (ISBN)
Available from: 2007-09-21 Created: 2007-09-21 Last updated: 2017-11-27
Olsson, B., Gawronska, B., Erlendsson, B., Lindlöf, A. & Dura, E. (2006). Automated text analysis of biomedical abstracts applied to the extraction of signaling pathways involved in plant cold-adaptation. In: N. Kolchanov, R. Hofestadt (Ed.), Proceedings of the Fifth International Conference on Bioinformatics of Genome Regulation and Structure: Volume 3. Paper presented at 5th International Conference on Bioinformatics of Genome Regulation and Structure, Novosibirsk, Russia, July 16-22, 2006 (pp. 296-299). Russian Academy of Sciences
Open this publication in new window or tab >>Automated text analysis of biomedical abstracts applied to the extraction of signaling pathways involved in plant cold-adaptation
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2006 (English)In: Proceedings of the Fifth International Conference on Bioinformatics of Genome Regulation and Structure: Volume 3 / [ed] N. Kolchanov, R. Hofestadt, Russian Academy of Sciences, 2006, p. 296-299Conference paper, Published paper (Other academic)
Abstract [en]

Motivation: Automated text analysis is an important tool for facilitating the extraction of knowledge from biomedical abstracts, thereby enabling researchers to build pathway models that integrate and summarize information from a large number of sources. Advanced methods of in-depth analysis of texts using grammar-based approaches developed within the field of computational linguistics must be adapted to the special requirements and challenges posed by biomedical texts, so that these methods can be made available to the bioinformatics and computational biology communities. Results: Our system for automated text analysis and extraction of pathway information is here applied to a set of PubMed abstracts concerning the CBF signaling pathway, which is a key pathway involved in the cold-adaptation response of plants subjected to cold non-freezing temperatures. The system successfully and accurately re-discovers the main features of this pathway, while also pointing to interesting and plausible new hypotheses. The evaluation also reveals a number of issues which will be important targets in the continued development of the system, e.g. the need for an extended lexicon of taxonomic terms and an improved procedure for recognition of sentence boundaries.

Place, publisher, year, edition, pages
Russian Academy of Sciences, 2006
Identifiers
urn:nbn:se:his:diva-1928 (URN)000243859500067 ()5-7692-0848-1 (ISBN)978-5-7692-0848-5 (ISBN)
Conference
5th International Conference on Bioinformatics of Genome Regulation and Structure, Novosibirsk, Russia, July 16-22, 2006
Available from: 2007-09-21 Created: 2007-09-21 Last updated: 2018-08-31Bibliographically approved
Olsson, B., Gawronska, B. & Erlendsson, B. (2006). Deriving pathway maps from automated text analysis: a grammar-based approach. In: Mikhail S. Gelfand, Vsevolod J. Makeev, Mireille Regnier (Ed.), International Moscow Conference on Computational Molecular Biology 2005. Paper presented at International Moscow Conference on Computational Molecular Biology (MCCMB'2005), July 18-21, 2005, Moscow, Russia (pp. 268-270). Imperial College Press
Open this publication in new window or tab >>Deriving pathway maps from automated text analysis: a grammar-based approach
2006 (English)In: International Moscow Conference on Computational Molecular Biology 2005 / [ed] Mikhail S. Gelfand, Vsevolod J. Makeev, Mireille Regnier, Imperial College Press, 2006, p. 268-270Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Imperial College Press, 2006
Identifiers
urn:nbn:se:his:diva-1715 (URN)
Conference
International Moscow Conference on Computational Molecular Biology (MCCMB'2005), July 18-21, 2005, Moscow, Russia
Available from: 2007-08-20 Created: 2007-08-20 Last updated: 2017-11-27Bibliographically approved
Olsson, B., Gawronska, B. & Erlendsson, B. (2006). Deriving pathway maps from automated text analysis using a grammar-based approach. Journal of Bioinformatics and Computational Biology, 4(2), 483-501
Open this publication in new window or tab >>Deriving pathway maps from automated text analysis using a grammar-based approach
2006 (English)In: Journal of Bioinformatics and Computational Biology, ISSN 0219-7200, E-ISSN 1757-6334, Vol. 4, no 2, p. 483-501Article in journal (Refereed) Published
Abstract [en]

We demonstrate how automated text analysis can be used to support the large-scale analysis of metabolic and regulatory pathways by deriving pathway maps from textual descriptions found in the scientific literature. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. Our method uses an algorithm that searches through the syntactic trees produced by a parser based on a Referent Grammar formalism, identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses). The semantic categories used in the classification are based on the relation set used in KEGG (Kyoto Encyclopedia of Genes and Genomes), so that pathway maps using KEGG notation can be automatically generated. We present the current version of the relation extraction algorithm and an evaluation based on a corpus of abstracts obtained from PubMed. The results indicate that the method is able to combine a reasonable coverage with high accuracy. We found that 61% of all sentences were parsed, and 97% of the parse trees were judged to be correct. The extraction algorithm was tested on a sample of 300 parse trees and was found to produce correct extractions in 90.5% of the cases.

Place, publisher, year, edition, pages
World Scientific, 2006
Identifiers
urn:nbn:se:his:diva-1858 (URN)10.1142/S0219720006002041 (DOI)2-s2.0-33745684308 (Scopus ID)
Available from: 2007-09-12 Created: 2007-09-12 Last updated: 2017-12-12Bibliographically approved
Gawronska, B., Olsson, B. & Erlendsson, B. (2006). Towards an Automated Analysis of Biomedical Abstracts. In: Data Integration in the Life Sciences: Third International Workshop, DILS 2006 (pp. 50-65). Springer
Open this publication in new window or tab >>Towards an Automated Analysis of Biomedical Abstracts
2006 (English)In: Data Integration in the Life Sciences: Third International Workshop, DILS 2006, Springer, 2006, p. 50-65Conference paper, Published paper (Other academic)
Abstract [en]

An essential part of bioinformatic research concerns the iterative process of validating hypotheses by analyzing facts stored in databases and in published literature. This process can be enhanced by language technology methods, in particular by automatic text understanding. Since it is becoming increasingly difficult to keep up with the vast number of scientific articles being published, there is a need for more easily accessible representations of the current knowledge. The goal of the research described in this paper is to develop a system aimed to support the large-scale research on metabolic and regulatory pathways by extracting relations between biological objects from descriptions found in literature. We present and evaluate the procedures for semantico-syntactic tagging, dividing the text into parts concerning previous research and current research, syntactic parsing, and transformation of syntactic trees into logical representations similar to the pathway graphs utilized in the Kyoto Encyclopaedia of Genes and Genomes.

Place, publisher, year, edition, pages
Springer, 2006
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 4075
National Category
Engineering and Technology
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-1917 (URN)10.1007/11799511_6 (DOI)000239622300004 ()2-s2.0-33746718080 (Scopus ID)978-3-540-36593-8 (ISBN)
Available from: 2007-09-21 Created: 2007-09-21 Last updated: 2017-11-27Bibliographically approved
Dura, E., Gawronska, B., Olsson, B. & Erlendsson, B. (2006). Towards Information Fusion in Pathway Evaluation: Encoding Relations in Biomedical Texts. In: The 9th International Conference on Information Fusion: Florence, Italy, 10-13 July 2006 (pp. 240-247). IEEE Press
Open this publication in new window or tab >>Towards Information Fusion in Pathway Evaluation: Encoding Relations in Biomedical Texts
2006 (English)In: The 9th International Conference on Information Fusion: Florence, Italy, 10-13 July 2006, IEEE Press, 2006, p. 240-247Conference paper, Published paper (Other academic)
Abstract [en]

The long-term goal of the research presented in this paper is to incorporate linguistic text analysis into a system for evaluation of biological pathways. In this system, relations extracted from biomedical texts will be compared with pathways encoded in existing specialized databases. In this way, the biologist's conclusions regarding the plausibility and/or novelty of a certain relation between genes, proteins, etc., can be supported by fused information from biological databases and biological literature. We aim at overcoming the shortcomings of existing systems for information retrieval by proposing a method based on thorough linguistic analysis of a large text corpus. In this paper, we present a comparative analysis of two corpora: one consisting of biomedical texts from PubMed, the other one of general English prose. The results stress the importance of taking multiword entries into account when constructing a system for extracting biological relations from texts

Place, publisher, year, edition, pages
IEEE Press, 2006
Identifiers
urn:nbn:se:his:diva-1916 (URN)10.1109/ICIF.2006.301666 (DOI)000245998000106 ()2-s2.0-50149093482 (Scopus ID)0-9721844-6-5 (ISBN)
Available from: 2007-09-21 Created: 2007-09-21 Last updated: 2017-11-27
Gawronska, B. & Erlendsson, B. (2005). Syntactic, Semantic and Referential Patterns in Biomedical Texts: towards in-depth text comprehension for the purpose of bioinformatics. In: Bernadette Sharp (Ed.), Natural Language Understanding and Cognitive Science, Proceedings of the 2nd International Workshop on Natural Language Understanding and Cognitive Science, NLUCS 2005, In conjunction with ICEIS 2005, Miami, FL, USA, May 2005: . Paper presented at 2nd International Workshop on Natural Language Understanding and Cognitive Science, NLUCS 2005, in Conjunction with ICEIS 2005; Miami, FL; 24 May 2005 through 24 May 2005 (pp. 68-77). INSTICC Press
Open this publication in new window or tab >>Syntactic, Semantic and Referential Patterns in Biomedical Texts: towards in-depth text comprehension for the purpose of bioinformatics
2005 (English)In: Natural Language Understanding and Cognitive Science, Proceedings of the 2nd International Workshop on Natural Language Understanding and Cognitive Science, NLUCS 2005, In conjunction with ICEIS 2005, Miami, FL, USA, May 2005 / [ed] Bernadette Sharp, INSTICC Press, 2005, p. 68-77Conference paper, Published paper (Refereed)
Abstract [en]

An essential part of bioinformatic research concerns the iterative process of validating hypotheses by analyzing facts stored in databases and in published literature. This process can be enhanced by automatic in-depth text understanding. A prerequisite for this is an adequate syntactic and semantic analysis. The paper presents the results of syntactic, semantic, and textual analysis of a corpus of biomedical abstracts. It focuses on the ways in which relevant molecular interactions are referred to in the abstracts, and proposes a strategy for linking natural language expressions to the standard notation used in Kyoto Encyclopedia of Genes and Genomes. The syntactic and semantic regularities observed in the language of biomedicine are also discussed from the cognitive point of view.

Place, publisher, year, edition, pages
INSTICC Press, 2005
Keywords
Biomedical abstracts, Biomedical text, Iterative process, Natural language expressions, Semantic analysis, Standard notation, Text comprehensions, Textual analysis
Identifiers
urn:nbn:se:his:diva-1650 (URN)10.5220/0002566900680077 (DOI)2-s2.0-33745695457 (Scopus ID)972-8865-23-6 (ISBN)978-972-8865-23-8 (ISBN)
Conference
2nd International Workshop on Natural Language Understanding and Cognitive Science, NLUCS 2005, in Conjunction with ICEIS 2005; Miami, FL; 24 May 2005 through 24 May 2005
Available from: 2007-08-06 Created: 2007-08-06 Last updated: 2018-09-04Bibliographically approved
Gawronska, B., Erlendsson, B. & Olsson, B. (2005). Tracking biological relations in texts: a Referent Grammar based approach. In: Proceedings of the workshop Biomedical Ontologies and Text Processing, in connection to ECCB/05: 4th European Conference on Computational Biology. Paper presented at 4th European Conference on Computational Biology, Madrid, Spain, September 28 - October 1, 2005 (pp. 15-22).
Open this publication in new window or tab >>Tracking biological relations in texts: a Referent Grammar based approach
2005 (English)In: Proceedings of the workshop Biomedical Ontologies and Text Processing, in connection to ECCB/05: 4th European Conference on Computational Biology, 2005, p. 15-22Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we describe a method for extracting biological relations (in the first place, relations used in the KEGG ontology of biological pathways) from scientific texts. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. We propose an algorithm that searches through the syntactic trees produced by a parser based on a formalism called Referent Grammar (inspired by Categorial Grammar), identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses).

Identifiers
urn:nbn:se:his:diva-1759 (URN)
Conference
4th European Conference on Computational Biology, Madrid, Spain, September 28 - October 1, 2005
Available from: 2007-10-10 Created: 2007-10-10 Last updated: 2018-09-03Bibliographically approved
Gawronska, B., Torstensson, N. & Erlendsson, B. (2004). Defining and Classifying Space Builders for Information Extraction. In: Natural Language Understanding and Cognitive Science: Proceedings of the 1st International Workshop on Natural Language Understanding and Cognitive Science, NLUCS 2004. In conjunction with ICEIS 2004, Porto, Portugal, April 2004 (pp. 15-27).
Open this publication in new window or tab >>Defining and Classifying Space Builders for Information Extraction
2004 (English)In: Natural Language Understanding and Cognitive Science: Proceedings of the 1st International Workshop on Natural Language Understanding and Cognitive Science, NLUCS 2004. In conjunction with ICEIS 2004, Porto, Portugal, April 2004, 2004, p. 15-27Conference paper, Published paper (Other academic)
Identifiers
urn:nbn:se:his:diva-2196 (URN)972-8865-05-8 (ISBN)
Available from: 2007-07-06 Created: 2007-07-06 Last updated: 2017-11-27Bibliographically approved
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