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Literature-driven, Ontology-centric Knowledge Navigation for Lipidomics

by: Rajarama Kanagasabai, Hong Sang Low, Wee Tiong Ang, Anitha Veeramani, Markus Wenk, and Christopher Baker

In: Proceedings of the Workshop on the First Industrial Results of Semantic Technologies FIRST2007 at ISWC/ASWC2007, Busan, South Korea (November 2007) .

Abstract

As the semantic web vision continues to proliferate a gap still remains in the full scale adoption of such technologies. The exact reasons for this continue to be the subject of ongoing debate, however, it is likely the emergence of reproducible infrastructure and deployments will expedite its adoption. We illustrate the recognizable added value to life science researchers gained through the convergence of existing and customized semantic web technologies content acquisition pipelines supplying legacy unstructured texts, natural language processing, OWL-DL ontology development and instantiation, reasoning over A-boxes using a visual query tool. The resulting platform allows lipidomic researchers to rapidly navigate large volumes of full-text scientific documents according to recognizable lipid nomenclature, hierarchies and classifications. Specifically we have enabled searches for sentences describing lipid-protein and lipid-disease interactions.

BibTeX record

@inproceedings{Kanagasabai/2007/Literature-driven,
  abstract = {As the semantic web vision continues to proliferate a gap still remains in the full scale adoption of such technologies. The exact reasons for this continue to be the subject of ongoing debate, however, it is likely the emergence of reproducible infrastructure and deployments will expedite its adoption. We illustrate the recognizable added value to life science researchers gained through the  convergence of existing and customized semantic web technologies (content acquisition pipelines supplying legacy unstructured texts,  natural language processing, OWL-DL ontology development and instantiation, reasoning over A-boxes using a visual query tool). The resulting platform allows lipidomic researchers to rapidly navigate large volumes of full-text scientific documents according to recognizable lipid nomenclature, hierarchies and classifications. Specifically we have enabled searches for sentences describing lipid-protein and lipid-disease interactions.},
  added-at = {2007-11-07T19:18:42.000+0100},
  author = {Kanagasabai, Rajarama and Low, Hong Sang and Ang, Wee Tiong and Veeramani, Anitha and Wenk, Markus and Baker, Christopher},
  biburl = {http://www.bibsonomy.org/bibtex/2d2966e57d01b4f49a3f45da643959145/iswc2007},
  booktitle = {Proceedings of the Workshop on the First Industrial Results of Semantic Technologies (FIRST2007) at ISWC/ASWC2007, Busan, South Korea},
  crossref = {http://data.semanticweb.org/workshop/first/2007/proceedings},
  editor = {Cuel, Roberta and Nixon, Lyndon J B and Bergamini, Claudio},
  interhash = {654adf53d2b2744454ea31a3a8bd99e3},
  intrahash = {d2966e57d01b4f49a3f45da643959145},
  keywords = {2007 iswc knowledge navigation workshop_first},
  month = {November},
  timestamp = {2007-11-07T19:18:42.000+0100},
  title = {Literature-driven, Ontology-centric Knowledge Navigation for Lipidomics},
  year = 2007
}

Endnote record

%0 Conference Paper
%1 Kanagasabai/2007/Literature-driven
%A Kanagasabai, Rajarama
%A Low, Hong Sang
%A Ang, Wee Tiong
%A Veeramani, Anitha
%A Wenk, Markus
%A Baker, Christopher
%B Proceedings of the Workshop on the First Industrial Results of Semantic Technologies (FIRST2007) at ISWC/ASWC2007, Busan, South Korea
%D 2007
%E Cuel, Roberta
%E Nixon, Lyndon J B
%E Bergamini, Claudio
%K 
%T Literature-driven, Ontology-centric Knowledge Navigation for Lipidomics
%X As the semantic web vision continues to proliferate a gap still remains in the full scale adoption of such technologies. The exact reasons for this continue to be the subject of ongoing debate, however, it is likely the emergence of reproducible infrastructure and deployments will expedite its adoption. We illustrate the recognizable added value to life science researchers gained through the  convergence of existing and customized semantic web technologies (content acquisition pipelines supplying legacy unstructured texts,  natural language processing, OWL-DL ontology development and instantiation, reasoning over A-boxes using a visual query tool). The resulting platform allows lipidomic researchers to rapidly navigate large volumes of full-text scientific documents according to recognizable lipid nomenclature, hierarchies and classifications. Specifically we have enabled searches for sentences describing lipid-protein and lipid-disease interactions.