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You searched for subject:(Molecular Event Extraction). Showing records 1 – 2 of 2 total matches.

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University of Manchester

1. Sarafraz, Farzaneh. Finding conflicting statements in the biomedical literature.

Degree: PhD, 2012, University of Manchester

The main archive of life sciences literature currently contains more than 18,000,000 references, and it is virtually impossible for any human to stay up-to-date with this large number of papers, even in a specific sub-domain. Not every fact that is reported in the literature is novel and distinct. Scientists report repeat experiments, or refer to previous findings. Given the large number of publications, it is not surprising that information on certain topics is repeated over a number of publications. From consensus to contradiction, there are all shades of agreement between the claimed facts in the literature, and considering the volume of the corpus, conflicting findings are not unlikely. Finding such claims is particularly interesting for scientists, as they can present opportunities for knowledge consolidation and future investigations. In this thesis we present a method to extract and contextualise statements about molecular events as expressed in the biomedical literature, and to find those that potentially conflict each other. The approach uses a system that detects event negations and speculation, and combines those with contextual features (e.g. type of event, species, and anatomical location) to build a representational model for establishing relations between different biological events, including relations concerning conflicts. In the detection of negations and speculations, rich lexical, syntactic, and semantic features have been exploited, including the syntactic command relation. Different parts of the proposed method have been evaluated in a context of the BioNLP 09 challenge. The average F-measures for event negation and speculation detection were 63% (with precision of 88%) and 48% (with precision of 64%) respectively. An analysis of a set of 50 extracted event pairs identified as potentially conflicting revealed that 32 of them showed some degree of conflict (64%); 10 event pairs (20%) needed a more complex biological interpretation to decide whether there was a conflict. We also provide an open source integrated text mining framework for extracting events and their context on a large-scale basis using a pipeline of tools that are available or have been developed as part of this research, along with 72,314 potentially conflicting molecular event pairs that have been generated by mining the entire body of accessible biomedical literature. We conclude that, whilst automated conflict mining would need more comprehensive context extraction, it is feasible to provide a support environment for biologists to browse potential conflicting statements and facilitate data and knowledge consolidation.

Subjects/Keywords: 006.312; Text Mining; Natural Language Processing; Information Extraction; Biomedical Text Mining; Bioinformatics; Negation; Contradiction; Contrast; Literature-based discovery; Molecular Event Extraction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sarafraz, F. (2012). Finding conflicting statements in the biomedical literature. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/finding-conflicting-statements-in-the-biomedical-literature(963e490a-eeea-4f4c-864d-fb318899beed).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553430

Chicago Manual of Style (16th Edition):

Sarafraz, Farzaneh. “Finding conflicting statements in the biomedical literature.” 2012. Doctoral Dissertation, University of Manchester. Accessed August 07, 2020. https://www.research.manchester.ac.uk/portal/en/theses/finding-conflicting-statements-in-the-biomedical-literature(963e490a-eeea-4f4c-864d-fb318899beed).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553430.

MLA Handbook (7th Edition):

Sarafraz, Farzaneh. “Finding conflicting statements in the biomedical literature.” 2012. Web. 07 Aug 2020.

Vancouver:

Sarafraz F. Finding conflicting statements in the biomedical literature. [Internet] [Doctoral dissertation]. University of Manchester; 2012. [cited 2020 Aug 07]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/finding-conflicting-statements-in-the-biomedical-literature(963e490a-eeea-4f4c-864d-fb318899beed).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553430.

Council of Science Editors:

Sarafraz F. Finding conflicting statements in the biomedical literature. [Doctoral Dissertation]. University of Manchester; 2012. Available from: https://www.research.manchester.ac.uk/portal/en/theses/finding-conflicting-statements-in-the-biomedical-literature(963e490a-eeea-4f4c-864d-fb318899beed).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553430

2. Sarafraz, Farzaneh. Finding Conflicting Statements in the Biomedical Literature.

Degree: 2012, University of Manchester

The main archive of life sciences literature currently contains more than 18,000,000 references, and it is virtually impossible for any human to stay up-to-date with this large number of papers, even in a specific sub-domain.Not every fact that is reported in the literature is novel and distinct. Scientists report repeat experiments, or refer to previous findings. Given the large number of publications, it is not surprising that information on certain topics is repeated over a number of publications. From consensus to contradiction, there are all shades of agreement between the claimed facts in the literature, and considering the volume of the corpus, conflicting findings are not unlikely. Finding such claims is particularly interesting for scientists, as they can present opportunities for knowledge consolidation and future investigations.In this thesis we present a method to extract and contextualise statements about molecular events as expressed in the biomedical literature, and to find those that potentially conflict each other. The approach uses a system that detects event negations and speculation, and combines those with contextual features (e.g. type of event, species, and anatomical location) to build a representational model for establishing relations between different biological events, including relations concerning conflicts. In the detection of negations and speculations, rich lexical, syntactic, and semantic features have been exploited, including the syntactic command relation.Different parts of the proposed method have been evaluated in a context of the BioNLP 09 challenge. The average F-measures for event negation and speculation detection were 63% (with precision of 88%) and 48% (with precision of 64%) respectively. An analysis of a set of 50 extracted event pairs identified as potentially conflicting revealed that 32 of them showed some degree of conflict (64%); 10 event pairs (20%) needed a more complex biological interpretation to decide whether there was a conflict.We also provide an open source integrated text mining framework for extracting events and their context on a large-scale basis using a pipeline of tools that are available or have been developed as part of this research, along with 72,314 potentially conflicting molecular event pairs that have been generated by mining the entire body of accessible biomedical literature.We conclude that, whilst automated conflict mining would need more comprehensive context extraction, it is feasible to provide a support environment for biologists to browse potential conflicting statements and facilitate data and knowledge consolidation. Advisors/Committee Members: Nenadic, Goran.

Subjects/Keywords: Text Mining; Natural Language Processing; Information Extraction; Biomedical Text Mining; Bioinformatics; Negation; Contradiction; Contrast; Literature-based discovery; Molecular Event Extraction

extraction of contextualised molecular event information from textual data using state-of-the-art… …facts. • A hybrid machine learning and rule-based method for molecular event extraction… …results from molecular event extraction and contextualisation described in Chapter 3, along with… …89 Figure 3.1: An overview of the event extraction pipeline… …3.8: Overview of the event extraction system, Evemole...........................124 Figure… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sarafraz, F. (2012). Finding Conflicting Statements in the Biomedical Literature. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:157382

Chicago Manual of Style (16th Edition):

Sarafraz, Farzaneh. “Finding Conflicting Statements in the Biomedical Literature.” 2012. Doctoral Dissertation, University of Manchester. Accessed August 07, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:157382.

MLA Handbook (7th Edition):

Sarafraz, Farzaneh. “Finding Conflicting Statements in the Biomedical Literature.” 2012. Web. 07 Aug 2020.

Vancouver:

Sarafraz F. Finding Conflicting Statements in the Biomedical Literature. [Internet] [Doctoral dissertation]. University of Manchester; 2012. [cited 2020 Aug 07]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:157382.

Council of Science Editors:

Sarafraz F. Finding Conflicting Statements in the Biomedical Literature. [Doctoral Dissertation]. University of Manchester; 2012. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:157382

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