| 1. |
- Dura, Elzbieta, et al.
(författare)
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Towards Information Fusion in Pathway Evaluation : Encoding Relations in Biomedical Texts
- 2006
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Ingår i: 9th International Conference on Information Fusion. - : IEEE. - 9781424409532
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Konferensbidrag (refereegranskat)abstract
- 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
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| 2. |
- Gawronska, Barbara, et al.
(författare)
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Natural Language Technology In Multi-Source Information Fusion
- 2004
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Ingår i: Proceedings of the International IPSI-2004k Conference. - 8674661173
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Konferensbidrag (refereegranskat)abstract
- Information Fusion encompasses "the theory, techniques and tools conceived for exploiting the synergy in the information acquired from multiple sources" [http://www.inforfusion.org/mission.htm]. The main issue is to improve the quality of decisions utilizing several information sources (databases, sensors, simulations). Research on information fusion has focused on applications like robotics and command and control systems, but the need of information synergy concerns more and more fields. Natural language serves as important information source in all areas of human activity, but the integration of language into fusion systems is far from satisfactory. The paper discusses employing language technology in bioinformatics, and in industrial processes.
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| 3. |
- Gawronska, Barbara, et al.
(författare)
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Towards an Automated Analysis of Biomedical Abstracts
- 2006
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Ingår i: Data Integration in the Life Sciences. - Berlin, Heidelberg : Springer. - 9783540365938 ; , s. 50-65
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 4. |
- Gawronska, Barbara, et al.
(författare)
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Tracking biological relations in texts : a Referent Grammar based approach
- 2005
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Ingår i: Proceedings of the workshop Biomedical Ontologies and Text Processing, in connection to ECCB/05. ; , s. 15-22
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Konferensbidrag (refereegranskat)abstract
- 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).
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| 5. |
- Olsson, Björn, et al.
(författare)
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An Information Fusion Approach to Controlling Complexity in Bioinformatics Research
- 2005
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Ingår i: 2005 IEEE Computational Systems Bioinformatics Conference: Workshops & Poster Abstracts. - : IEEE Computer Society. - 0769524427 ; , s. 299-304
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Konferensbidrag (refereegranskat)abstract
- Information Fusion (IF) is about combining, or fusing, information from different sources in order to facilitate our understanding of a complex system and thereby provide insights that could not be gained from any of the individual data sources in isolation. We argue in this paper that there is a need for applying an IF approach in bioinformatics research, since the aim of bioinformatics is to understand complex biological systems using many different data sources providing complementary views of the system. We illustrate this argument with two application examples, where IF-based bioinformatics is applied to the study of stem cell differentiation and lipid digestion, respectively. We also discuss the use of automated information extraction from text sources, which is an essential component of a bioinformatics IF approach, given the abundant literature.
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| 6. |
- Olsson, Björn, et al.
(författare)
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Automated text analysis of biomedical abstracts applied to the extraction of signaling pathways involved in plant cold-adaptation
- 2006
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Ingår i: Proceedings of the Fifth International Conference on Bioinformatics of Genome Regulation and Structure. - : Russian Academy of Sciences. - 5769208481 - 9785769208485 ; , s. 296-299
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- 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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| 7. |
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| 8. |
- Olsson, Björn, et al.
(författare)
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Deriving pathway maps from automated text analysis using a grammar-based approach
- 2006
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Ingår i: Journal of Bioinformatics and Computational Biology. - : World Scientific. - 0219-7200 .- 1757-6334. ; 4:2, s. 483-501
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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