Biocuration2012 poster P113
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T EXT M INING A SSISTANTS IN W IKIS FOR B IOCURATION Bahar Sateli 1 , Caitlin Murphy 2 , René Witte 1 , Marie-Jean Meurs 1,2 and Adrian Tsang 2 1.Semantic Software Lab. & 2.Centre For Structural and Functional Genomics [{b_satel,mjmeurs}@encs,rwitte@cse,{cmurphy,tsang}@gene].concordia.ca Literature Curation Manually refining and updating bioinformatics databases Labor-intensive, error-prone and expensive task Web Crawler Spreadsheet Online Query Interface Database Curator WWW Downloaded Literature mycoMINE Natural Language Processing (NLP) techniques supporting Biofuel Research Process Experiments pH fungus (organism) substrate temperature buffer products enzyme gene specific activity substrate specificity and/or conditions conditions assay kinetic assay activity assay Automatic extraction of semantic entities and facts: z }| { z }| { Assay, Enzyme Activity Assay Conditions, Glycosylation Gene, Host Kinetic Assay Conditions, pH, Product Analysis Organism, Substrate SpecificActivity, Substrate Specificity, Temperature mycoMINE [1]: a text mining pipeline based on GATE [2]. mycoMINE Workflow Ontology Instantiated Processed Documents Populated Ontology for BRENDA External DBs: SwissProt, NCBI Grammar: Named Entity and Fact recognition Normalization: resolve ambiguities, abbreviations... Gazetteer: find matching entities, assign ontology classes NLP preprocessing: tokenisation, sentence splitting... Coreference Resolution: determine identical individuals Grounding: link to external DBs OWL Ontology Export mapping lists gazetteer lists GenWiki An NLP-enhanced wiki system based on the MediaWiki engine Seamlessly integrates NLP capabilities in a wiki environment Allows curators to discover knowledge embodied in the wiki content GenWiki User Interface Semantic Infrastructure NLP capabilities provided by the Semantic Assistants Framework [3] Brokers NLP pipelines as Web services Wiki-NLP communication through wiki plug-ins Database Wiki Ontologies Language Descriptions Service API Plug-in Web Server Graphical User Interface Rendering Engine Database Interface Client-Side Abstraction Layer Wiki-SA Connector Web Server NLP Service Connector JavaScript Wiki System Browser Semantic Assistants Service Information Service Invocation Publications [1] MJ. Meurs, C. Murphy, I. Morgenstern, G. Butler, J. Powlowski, A. Tsang, and R. Witte, “Semantic Text Mining Support for Lignocellulose Research” BMC MIDM, Vol.12 Suppl.1, 2012, to appear [2] H. Cunningham et al., “TextProcessing with GATE (Version 6)”University of Sheffield, Department of Computer Science 2011 [3] R. Witte, T. Gitzinger, “Semantic Assistants –User-Centric Natural Language Processing Services for Desktop Clients”ASWC 2008, Bangkog, Thailand. Springer LNCS 5367, pp. 360–374 2009 Application Templating mechanism to present the NLP results to users Semantic metadata embedded in each page Using the Semantic MediaWiki (SMW) markup Semantic Entity Retrieval Retrieve literature that contain certain type of entities Using SMW inline queries {{#ask: [[ hasType::Enzyme]] | ?Enzyme = Enzyme Entities Found | format = table | headers = plain | default = No pages found! | mainlabel = Page Name }} Evaluation Methodology: Corpus of 15 documents Manually pre-filled GeneWiki with full-text papers Used mycoMINE to automatically extract relevant entities Keeping the track of time Average Curation Time: No Semantic Support vs. GenWiki Abstract Selection Full Paper No Support GenWiki No Support GenWiki 1 min. 20 sec. 37.5 min. 30.6 min. 67% ⇓ 20% ⇓ Conclusion GenWiki proves that seamless integration of NLP capabilities inside a wiki is indeed efficient, in terms of the time curators need to annotate and retrieve entities of interest from the domain literature. Acknowledgments Funding: Genome Canada & Génome Québec. Collaboration: Sherry Wu.
Transcript of Biocuration2012 poster P113
TEXT MINING ASSISTANTS IN WIKIS FOR BIOCURATIONBahar Sateli1, Caitlin Murphy2, René Witte1, Marie-Jean Meurs1,2 and Adrian Tsang2
1.Semantic Software Lab. & 2.Centre For Structural and Functional Genomics[{b_satel,mjmeurs}@encs,rwitte@cse,{cmurphy,tsang}@gene].concordia.ca
Literature CurationManually refining and updating bioinformatics databasesLabor-intensive, error-prone and expensive task
Web Crawler Spreadsheet Online Query Interface
Database
Curator
WWW
Downloaded Literature
mycoMINENatural Language Processing (NLP) techniques supporting
Biofuel Research
Process ExperimentspH
fungus(organism)
substrate
temperaturebuffer
products
enzyme
gene
specificactivity
substratespecificity
and/or
conditions
conditions
assay
kinetic assay
activity assay
Automatic extraction of semantic entities and facts:︷ ︸︸ ︷ ︷ ︸︸ ︷Assay, Enzyme Activity Assay Conditions, Glycosylation
Gene, Host Kinetic Assay Conditions, pH, Product AnalysisOrganism, Substrate Specific Activity, Substrate Specificity, Temperature
mycoMINE [1]: a text mining pipeline based on GATE [2].
mycoMINE Workflow
OntologyInstantiated
Processed DocumentsPopulated Ontology for
BRENDA
External DBs:
SwissProt, NCBI
Grammar: Named Entity and Fact recognition
Normalization: resolve ambiguities, abbreviations...
Gazetteer: find matching entities, assign ontology classes
NLP preprocessing: tokenisation, sentence splitting...
Coreference Resolution: determine identical individuals
Grounding: link to external DBs
OWL Ontology Export
mappinglists
gazetteerlists
GenWikiAn NLP-enhanced wiki system based on the MediaWiki engineSeamlessly integrates NLP capabilities in a wiki environmentAllows curators to discover knowledge embodied in the wiki content
GenWiki User Interface
Semantic InfrastructureNLP capabilities provided by the Semantic Assistants Framework [3]Brokers NLP pipelines as Web servicesWiki-NLP communication through wiki plug-ins
Database
Wiki
Ontologies
Language
Descriptions
Service
AP
I
Plu
g−
inWeb Server
Graphical User Interface
Rendering Engine
Database Interface
Clie
nt−
Sid
e A
bstra
ctio
n L
ayer
Wik
i−S
A C
on
necto
r
Web
Serv
er
NLP Service Connector
JavaScript
Wiki System
Browser
Semantic Assistants
Service Information
Service Invocation
Publications[1] MJ. Meurs, C. Murphy, I. Morgenstern, G. Butler, J. Powlowski, A. Tsang, and R. Witte, “Semantic Text Mining Support for Lignocellulose Research” BMC MIDM, Vol.12 Suppl.1, 2012, to appear
[2] H. Cunningham et al., “Text Processing with GATE (Version 6)”University of Sheffield, Department of Computer Science 2011
[3] R. Witte, T. Gitzinger, “Semantic Assistants –User-Centric Natural Language Processing Services for Desktop Clients”ASWC 2008, Bangkog, Thailand. Springer LNCS 5367, pp. 360–374 2009
ApplicationTemplating mechanism to present the NLP results to usersSemantic metadata embedded in each pageUsing the Semantic MediaWiki (SMW) markup
Semantic Entity RetrievalRetrieve literature that contain certain type of entitiesUsing SMW inline queries
{{#ask: [[ hasType::Enzyme]]| ?Enzyme = Enzyme Entities Found| format = table| headers = plain| default = No pages found!| mainlabel = Page Name}}
EvaluationMethodology:
Corpus of 15 documentsManually pre-filled GeneWiki with full-text papersUsed mycoMINE to automatically extract relevant entitiesKeeping the track of time
Average Curation Time: No Semantic Support vs. GenWiki
Abstract Selection Full PaperNo Support GenWiki No Support GenWiki
1 min. 20 sec. 37.5 min. 30.6 min.67% ⇓ 20% ⇓
ConclusionGenWiki proves that seamless integration of NLP capabilitiesinside a wiki is indeed efficient, in terms of the time curatorsneed to annotate and retrieve entities of interest from thedomain literature.
AcknowledgmentsFunding: Genome Canada & Génome Québec.Collaboration: Sherry Wu.
