Federating heterogeneous biological resources on the web: A case study on TRP channel ontology construction

Se Jin Nam, Jinhyun Ahn, Jin Muk Lim, Jae Hong Eom, Ju Hong Jeon, Hong Gee Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

TRP (Transient receptor potential) channel is a biological component which could be of factors in severe diseases such as heart attack and cancer. In order for researchers to easily search for protein-protein interactions for mammalian TRP channel, TRIP Database was created. However, TRIP Database does not contain information about proteins in details, making researchers in turn visit other database services such as UniProt and PDB. In this paper, we propose a semantic TRP Ontology made from TRIP Database, allowing users to be given the collected contents from other relevant databases as well using a single request. As a practical scenario, we generate RDF triples from TRIP Database by referring to TRP Ontology designed to have links with UniProt. A federated way of collecting contents from two different services is proposed.

Original languageEnglish
Title of host publicationSemantic Technology - Third Joint International Conference, JIST 2013, Revised Selected Papers
PublisherSpringer Verlag
Pages103-109
Number of pages7
ISBN (Print)9783319068251
DOIs
StatePublished - 2014
Event3rd Joint International Semantic Technology Conference, JIST 2013 - Seoul, Korea, Republic of
Duration: 28 Nov 201330 Nov 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8388 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd Joint International Semantic Technology Conference, JIST 2013
Country/TerritoryKorea, Republic of
CitySeoul
Period28/11/1330/11/13

Keywords

  • Ontology
  • SPARQL
  • TRP channel

Fingerprint

Dive into the research topics of 'Federating heterogeneous biological resources on the web: A case study on TRP channel ontology construction'. Together they form a unique fingerprint.

Cite this