Text and data mining

Text and data mining

• Textmining phenotypes (Rob H, Hongyan Wu, Yas; interested: S Kawashima, Tudor, R Vos, Mark W, S Kumagai, MichelD, interested: Joe Miyamoto)
  • Drug interactions and phenotypes
  • complex phenotypes
  • environment-phenotype interactions
  • host-pathogen interactions and phenotypes for infectious diseases
  • microbial phenotypes, environments, genetic information (add to MicrobeDB?)
  • Create a X Phenotype Ontology, X \in { frog, chicken, mosquito }
• Natural language processing, literature annotation and QA system
  • Interoperability of text mining/annotation resources (Tudor, interested: Takatomo, E. Bolton, Takeru Nakazato, Raoul, MarkT)
    • Goal
      • to collect annotations to Biomedical Literature
      • to align them
      • to make them publicly accessible
        • REST API
        • SPARQL endpoint
      • to find and develop appliations
    • Resources
      • PubTator REST API to become compatible with PubAnnotation Annotation Server API (Wei)
      • Phenotype annotation to be registered to PubAnnotation (Tudor)
      • TextAE to be used in Patient Archive and Orphanet Knowledge Management (Tudor)
      • DisGeNet annotation to be registered to PubAnnotation (Núria, Tudor)
      • EuropeanPMC - PubAnnotation Interoperability (Jee-Hyub)
      • Nanotea (Alex)
      • PubAnnotation - an open repository of literature annotation
  • Knowledge Graph Annotator for human curation (MarkT, Jee-Hyub, interested: E. Bolton)
    • Finished: bug fixes and working nanopub store interface
    • New feature ideas (many thanks to Nuria and Erick):
      • more authentication options, e.g. LinkedIn, Twitter, Scopus, ResearchID
      • options to store annotation (nanopub) in different locations
      • register type of evidence with ECO ontology, or
      • register source of evidence with PubAnnotation URL
    • In progress: RDFa bookmarklet to connect to the annotator from any html page
  • (Graph-based) data analytics on top of integrated text mining data sources (disease - gene - phenotype - chemical entities - species) (Tudor, interested: E. Bolton, Atsuko, Joe Miyamoto)
  • QA over LOD
    • Bio2RDF+UniProt setup for LODQA (Michel, Hongyan, Jin-Dong, Jerven, interested: E. Bolton)

Day 1&2

Text mining annotation interoperability (Text mining annotation alignment and analysis)

• Motivation
  • Various annotation projects sharing the same target, PubMed and PMC.
  • They are maintained in silos.
• Goal
  • To collect annotations to literature and align them
  • To estabilish interoperability between text annotation resources
  • To make them publicly accessible through dereferenceable URIs, REST API, RDF and SPARQL endpoints
  • To find and develop applications
• Participants
  • Wei, Tudor, Núria, Mark T., Jee-Hyub, Kevin, Alex G, Jin-Dong ...
• Started integration of several text mined data sets:
  • DisGeNET (diseases + genes)
  • PubTator (diseases + genes + variants + species)
  • HPO Pubmed annotations
  • DisGeRel? (diseases + genes)
• PubAnnotation to provide alignment and storage of annotation resources
• API-level interoperability
  • PubTator is interoperable with PubAnnotation at API level.
  • Phenotype CR
• Issues
  • How to represent document level annotation.
  • How to align concept labels (ontology alignment problem).
  • How to do the quality assessment.
• Goals:
• Naive comparison of text mined concepts - for quality purposes
• Detection of gaps between mined data and curated domain knowledge with focus on disease - gene - phenotype associations (e.g., inferring new phenotypes for rare disorders)
• Clustering of genes based on phenotypes and / or phenotypes based on genes - and perhaps going forward towards BPs | MFs, etc ... (integration with GO)

Day 4

API-level interoperability (con.)

• Manual curated MESH term annotation
  • Integrated the MeSH-PMIDs manual curated annotation in PubAnnotation.
    • E-utilites for accessing the title/abstract and MESH terms.
      • http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/PubAnnotationByMeSH.cgi
      • http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/PubAnnotationByPubTator.cgi
    • Disease/Chemical are recognized as two individual categories, otherwise are represented by the general category: "MESH".
    • Gang Fu used SPARQL to extract MeSH synonyms for string match.
    • Exact match with simple pre- and post-processing.
  • To-Do: separates genes, species as two individual categories from the general category.
  • Ex. http://textae.pubannotation.org/editor.html?mode=edit&target=http://pubannotation.org/projects/Test_MeSH/docs/sourcedb/PubMed/sourceid/9916105/annotations.json

Final Wrap-up

Literature annotation interoperability

Data interoperability

• Annotation data set deposited
  • PubmedHPO
  • DisGeNet
• Large data set interchange API to be developed.

API level interoperability

• PubAnnotation API for annotation interoperability
  • curl -d text="example text" URL_of_annotation_web_service
  • curl -d sourcedb="PubMed" -d sourceid="123456" URL_of_annotation_web_service
• PubTator: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/PubAnnotationByPubTator.cgi
• MESH: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/PubAnnotationByMeSH.cgi
• PhenoCR: http://phenocr.bio-lark.org:5555/pubannotation
• Demo: http://pubannotation.org/projects/Test_MeSH/docs/sourcedb/PubMed/sourceid/17175308
• Others
  • Enju dependency parser
  • Sentence segmentator
  • PubDictionaries
• Respository of PubAannotation-compatible tools to be developed

PubDictionaries - PubAnnotation application

• BioPortal dictionary is generated from BioPortal endpoint. (labing_properties_in_bioportal)
  • Dictionary URL: http://pubdictionaries.org/dictionaries/BioPortal
  • Lookup API: http://pubdictionaries.org/mapping/term_to_id?dictionaries=BioPortal&output_format=simple&threshold=0.6&top_n=0
  • Text annotation API: http://pubdictionaries.org/mapping/text_annotation?dictionaries=BioPortal&matching_method=approximate&max_tokens=6&min_tokens=1&threshold=0.6&top_n=0
• A sample text is annotated using the dictionary
  • http://pubannotation.org/projects/system-maintenance/docs/sourcedb/PMC/sourceid/13914/divs
• 10,000 PubMed articles are under annotation
  • http://pubannotation.org/projects/BioPortalExp (Tudor)

Question-Answering

• New version of LODQA released: http://lodqa.org
  • unstable at the moment but will be improved.
• Setting up for Bio2RDF and UniProt's begun.
  • not yet finished.

Phenotype data analytics

• Processed NCBI disease - gene corpus and the HPO annotation corpus - ~6.5Mio abstracts
• Results:
• Gene & GO BP annotations for 4,722 diseases
• HPO TF-IDF annotations for 4,691 diseases
• 7,666 HPO terms
• 10,438 GO BP terms
• Integrated: a large HP - GO BP association matrix based on additive TF-IDF scores

Textmining phenotypes

• Drug labels and human/mouse/rat phenotypes: first attempt at http://aber-owl.net/aber-owl/diseasephenotypes/drugs/

Knowledge graph annotation

• Knowledge Graph Annotator (contact MarkT; input from Erick, Nuria, Jee-Hyub, Wei, Jin-Dong, Gang, MarkW, Michel, ... -> Thank you!)
  • purpose: service for human curation directly on knowledge graph
    • UI
    • machine readable annotations
  • new name! Open Reusable Knowledge graph Annotator: “ORKA”
  • result 1: UI integration: partial implementation of Bookmarklet
    • extract RDFa triple statements (e.g. Virtuoso Facet Viewer)
    • display for user selection -> send to ORKA API
    • todo: better human readable labels
    • todo: look at alternative content representation
  • result 2: better back-end accessibility: nanopub store interface
  • result 3: bug fixes, but..
  • future work
    • evidence to point to PubAnnotation span (identifier)
    • query PubAnnotation for evidence suggestions
    • previous text-mining results in PubAnnotation <=> training, validation