• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Semantic annotation of biomedical data
 

Semantic annotation of biomedical data

on

  • 1,866 views

Presentation about semantic annotation of biomedical data. Presented at LIRMM, INRIA and other between 2008 and 2010.

Presentation about semantic annotation of biomedical data. Presented at LIRMM, INRIA and other between 2008 and 2010.

Statistics

Views

Total Views
1,866
Views on SlideShare
1,864
Embed Views
2

Actions

Likes
2
Downloads
74
Comments
1

1 Embed 2

http://localhost 2

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel

11 of 1 previous next

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
  • Very interesting, this looks similar to what I'm attempting for my MSc thesis, however in my case it's on a MUCH smaller scale :). I am currently looking at implementing an ontology-based semantic similarity measure for 'expansion' of semantic annotations. See my blog for more (unstructured) information: http://graus.nu/category/thesis/

    Can I find more information/publications about this particular project?
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • Let’s try to understand the context of this work and what we mean by semantic annotation.
  • Ontology based annotation is not wide-spread; possibly because of:Lack of a one stop shop for bio-ontologiesLack of tools to annotate datasetsManual  will not scaleAutomatic  can it be ‘good enough’?Lack of a sustainable mechanism to create ontology based annotations
  • They structure the knowledge from a domainThey specify terms that can be used by natural language processing algorithms to process textThey uniquely identify concept (URI)They specify relations between concepts that can be used for computing concept similarityThey define hierarchies allowing abstraction of typeThey play the role of common denominator for various data from a domain
  • Uses a dictionary (or lexicon): a list of strings that identifies ontology conceptsConstructed by accessing ontologies and pooling all concept names or other string forms (synonyms, labels) that syntactically identify conceptsWe use Mgrep, a syntactic concept recognizerDeveloped by University of Michigan – NCIBIHas a very high degree of accuracy (over 95% in recognizing disease names)Fast, scalable, domain independentAnother AMIA STB 2009 presentation (tomorrow, 1:50pm)Mgrep vs. MetaMap evaluation Higher precision & faster Not limited to UMLS terminologies
  • Performing a search of GEO using OBR. A user searching for “melanoma” in Bioportal is able to view the set of online data resources that have been annotated with the ontology terms related to this query. The GEO element “melanoma progression” is returned as a pertinent element for this search. (Note: In the current version, we have dealt only with element titles and descriptions to validate the notion of context awareness. Later, we will process the more of the metadata structure to enable a finer grained level of detail.) The display within BioPortal allows the user to view the original data set with a single click.
  • Specific evaluation with external users on progressCenter for Clinical and Translational InformaticsJackson LabUniv. of Indiana (research management system)
  • Let’s try to understand the context of this work and what we mean by semantic annotation.

Semantic annotation of biomedical data Semantic annotation of biomedical data Presentation Transcript