The Semantic Web and BioMarkers

18
The Semantic Web and BioMarkers Benjamin Good Wilkinson Laboratory iCAPTURE http:// bioinfo.icapture.ubc.ca/bgood

description

The Semantic Web and BioMarkers. Benjamin Good Wilkinson Laboratory iCAPTURE http://bioinfo.icapture.ubc.ca/bgood. Outline. Define Semantic Web Discuss Applications in Progress Ahab iCAPTURer Discuss needs from BBM team. The Semantic Web. - PowerPoint PPT Presentation

Transcript of The Semantic Web and BioMarkers

Page 1: The Semantic Web and BioMarkers

The Semantic Web and BioMarkers

Benjamin Good

Wilkinson Laboratory

iCAPTURE

http://bioinfo.icapture.ubc.ca/bgood

Page 2: The Semantic Web and BioMarkers

Outline

• Define Semantic Web

• Discuss Applications in Progress– Ahab– iCAPTURer

• Discuss needs from BBM team

Page 3: The Semantic Web and BioMarkers

The Semantic Web

“The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation.”

Tim Berners-Lee

Page 4: The Semantic Web and BioMarkers

Meaning Through Ontology

Animal

Mammal

Primate

Lemur HumanGorilla

Hair

Big MediumSmall

has

has_size

is_a

Hair

Hair

HairHair

Page 5: The Semantic Web and BioMarkers

Meaning Through Ontology

Web Services

Bioinformatics programs

Sequence Processing

Sequence Alignment

http://bioinfo.icapture.ubc.ca/bla123.cgi

DNA-Protein DNA-DNA

BLAST-X

Page 6: The Semantic Web and BioMarkers

Meaning Through Ontology

BiologicalProcess

Response to stimulus

Defense response

Immune response

Interleukin-10

Cellular component

Membrane

Plasma membrane

Page 7: The Semantic Web and BioMarkers

On a Semantic Web

• It is easier to find things.

• It is easier to identify similarity.

• It is easier to integrate information.

UCSC

FlyBase

Genbank

Gene Ontology

Page 8: The Semantic Web and BioMarkers

Gene Ontology (http://geneontology.org)

• (SW!) Applications listed

– 6 adding annotations– 9 miscellaneous – 14 searching and browsing– 36 for microarray analysis!

• Mostly for “summarizing the predominant biological theme of a given gene list”.

• Validation• Hypothesis generation

Page 9: The Semantic Web and BioMarkers

GO analysis

Page 10: The Semantic Web and BioMarkers

My Current Projects

• Ahab - A Semantic Web Browser

• iCAPTURer - an experimental system for collective ontology creation.

Page 11: The Semantic Web and BioMarkers

Ahab

Page 12: The Semantic Web and BioMarkers

Ahab

Page 13: The Semantic Web and BioMarkers

Ahab RDF

Page 14: The Semantic Web and BioMarkers

iCAPTURer

• Ontology generation

Is hard and takes a lot of time

Page 15: The Semantic Web and BioMarkers

iCAPTURer

• Divide and Conquer

Page 16: The Semantic Web and BioMarkers

iCAPTURer• A website that asks

volunteers the questions needed to build an ontology.

• Deployed with some success at the Young Investigators Forum for Research in Circulatory and Respiratory Health

Page 17: The Semantic Web and BioMarkers

My Needs

• More interaction with the scientists.– Motivate, clarify, and ultimately

enable my research.

• Participation from team members in future knowledge capture experiments.

• If possible, data and algorithms provided as BioMoby web services…

Page 18: The Semantic Web and BioMarkers

Thanks

http://bioinfo.icapture.ubc.ca/bgoodSlides available here under presentations.

• Wilkinson Laboratory– Mark– Clarence– Nina– Eddie

• BBM team– Martha– Janet– …