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| Zoe Lacroix, Sumedha Gholba, Herve Menager, "BioMap: Discovering Schema Mapping Using Ontologies," 2005 IEEE Computational Systems Bioinformatics Conference - Workshops, pp. 118-119, 2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05), 2005. | |||
| BibTex | x | ||
| @article{ 10.1109/CSBW.2005.31, author = {Zoe Lacroix and Sumedha Gholba and Herve Menager}, title = {BioMap: Discovering Schema Mapping Using Ontologies}, journal ={2005 IEEE Computational Systems Bioinformatics Conference - Workshops}, volume = {0}, year = {2005}, isbn = {0-7695-2442-7}, pages = {118-119}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSBW.2005.31}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2005 IEEE Computational Systems Bioinformatics Conference - Workshops TI - BioMap: Discovering Schema Mapping Using Ontologies SN - 0-7695-2442-7 SP118 EP119 A1 - Zoe Lacroix, A1 - Sumedha Gholba, A1 - Herve Menager, PY - 2005 KW - null VL - 0 JA - 2005 IEEE Computational Systems Bioinformatics Conference - Workshops ER - | |||
Biologists currently devote significant time and effort searching information for their research. The wide diversity in terminology used inhibit effective computerized and manual data retrieval. For example, say a user wants to ?nd all the gene products that are involved in bacterial protein synthesis, and that have sequences or structures significantly different from those in humans. If one database describes these molecules as being involved in ?translation?, whereas another uses the phrase ?protein synthesis?, it will be difficult for the user - and even harder for a computer - to find functionally equivalent terms. A schema mapping tool, which interprets results from one database in terminology used by a second database, can solve such problems. We started our project by developing schema mapping for UniProt1 and Genbank2 protein resources, both of which can be rendered in XML format, as a large part of scientific community uses proteomic resources. The approach will later on be extended to other scientific databases. Here we present a novel idea of mapping schemas using ontologies.