Tremendous amounts of data exist in life sciences along with many bio-ontologies. Though these databases contain important information about gene, proteins, functions, etc., this information is not well utilized due to the heterogeneous formats of these databases. Therefore, ontology alignment (OA) is now very critical for life science domain. Our work utilizes AgreementMaker for OA and describes results, difficulties faced in the process, and lessons learned. We aligned two real-world ontologies, the Parasite Experiment Ontology (PEO) and the Ontology for Biomedical Investigations (OBI). The former is more applicationoriented and the latter is a reference ontology for any biomedical or clinical investigations. Our study led to several enhancements to AgreementMaker: annotation profiling, mapping provenance information, and tailored lexicon building. These enhancements, which are applicable to any OA system, greatly improved the alignment of these real world ontologies, producing 90% precision with 60% recall from the BSM, the Base Similarity Matcher, and 57% precision with 67% recall from the PSM, the Parametric String Matcher, both using lexicon lookup for synonyms. The mappings obtained through this study are posted on BioPortal site for public use. † Partially supported by NSF Awards IIS–0513553 and IIS-0812258 and by the Intelligence Advanced Research Projects Activity (IARPA) via Air Force Research Laboratory (AFRL) contract number FA8650-10-C-7061. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, AFRL, or the U.S. Government.
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