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Literature-driven, Ontology-centric Knowledge Navigation for Lipidomics

by: Rajarama Kanagasabai and Hong Sang Low and Wee Tiong Ang and Anitha Veeramani and 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,
  author = {Rajarama Kanagasabai and Hong Sang Low and Wee Tiong Ang and Anitha Veeramani and Markus Wenk and Christopher Baker},
  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 = {Roberta Cuel and Lyndon J B Nixon and Claudio Bergamini},
  interHash = {654adf53d2b2744454ea31a3a8bd99e3},
  intraHash = {d2966e57d01b4f49a3f45da643959145},
  title = {Literature-driven, Ontology-centric Knowledge Navigation for Lipidomics},
  year = {2007},
  month = {November},
  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.}
}

Endnote record

%0 Conference Paper
%1 Kanagasabai/2007/Literature-driven
%A Rajarama Kanagasabai
%A Hong Sang Low
%A Wee Tiong Ang
%A Anitha Veeramani
%A Markus Wenk
%A Christopher Baker
%B Proceedings of the Workshop on the First Industrial Results of Semantic Technologies (FIRST2007) at ISWC/ASWC2007, Busan, South Korea
%D 2007
%E Roberta Cuel
%E Lyndon J B Nixon
%E Claudio Bergamini
%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.