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  • 1. Dura, Elzbieta
    et al.
    Gawronska, Barbara
    University of Skövde, School of Humanities and Informatics.
    Olsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Towards Information Fusion in Pathway Evaluation: Encoding Relations in Biomedical Texts2006In: The 9th International Conference on Information Fusion: Florence, Italy, 10-13 July 2006, IEEE Press, 2006, p. 240-247Conference 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

  • 2.
    Gawronska, Barbara
    et al.
    University of Skövde, School of Humanities and Informatics.
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Syntactic, Semantic and Referential Patterns in Biomedical Texts: towards in-depth text comprehension for the purpose of bioinformatics2005In: 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 (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.

  • 3.
    Gawronska, Barbara
    et al.
    University of Skövde, School of Humanities and Informatics.
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Olsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Tracking biological relations in texts: a Referent Grammar based approach2005In: 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 (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).

  • 4.
    Gawronska, Barbara
    et al.
    University of Skövde, School of Humanities and Informatics.
    Nikolayenkova, O
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    A corpus based analysis of English, Swedish, Polish, and Russian prepositions2006In: ISCA Tutorial and Research Workshop on Experimental Linguistics, 2006, p. 137-140Conference 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

  • 5.
    Gawronska, Barbara
    et al.
    University of Skövde, School of Humanities and Informatics.
    Olsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Towards an Automated Analysis of Biomedical Abstracts2006In: Data Integration in the Life Sciences: Third International Workshop, DILS 2006, Springer, 2006, p. 50-65Conference 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.

  • 6.
    Gawronska, Barbara
    et al.
    University of Skövde, School of Humanities and Informatics.
    Torstensson, Niklas
    University of Skövde, School of Humanities and Informatics.
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Defining and Classifying Space Builders for Information Extraction2004In: 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 (Other academic)
  • 7.
    Olsson, Björn
    et al.
    University of Skövde, School of Humanities and Informatics.
    Gawronska, Barbara
    University of Skövde, School of Humanities and Informatics.
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Deriving pathway maps from automated text analysis: a grammar-based approach2006In: 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 (Refereed)
  • 8.
    Olsson, Björn
    et al.
    University of Skövde, School of Humanities and Informatics.
    Gawronska, Barbara
    University of Skövde, School of Humanities and Informatics.
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Deriving pathway maps from automated text analysis using a grammar-based approach2006In: Journal of Bioinformatics and Computational Biology, ISSN 0219-7200, E-ISSN 1757-6334, Vol. 4, no 2, p. 483-501Article in journal (Refereed)
    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.

  • 9.
    Olsson, Björn
    et al.
    University of Skövde, School of Humanities and Informatics.
    Gawronska, Barbara
    University of Skövde, School of Humanities and Informatics.
    Erlendsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Lindlöf, Angelica
    University of Skövde, School of Humanities and Informatics.
    Dura, Elzbieta
    University of Skövde, School of Humanities and Informatics.
    Automated text analysis of biomedical abstracts applied to the extraction of signaling pathways involved in plant cold-adaptation2006In: 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 (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.

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