TY - GEN
T1 - Pharmacological class data representation in the Web Ontology Language (OWL)
AU - Zhu, Qian
AU - Tao, Cui
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - Dozens of drug terminologies and resources capture drug and/or drug class information; they range greatly in their coverage and their adequacy of representation. However, there are no transformative ways to link these resources together in a standard and formal fashion, which hinders data integration and data representation for supporting drug-related clinical and translational studies. In this study, we generated a standardized Pharmacological Class Profile Ontology, named PCPO, which integrates multiple drug resources in the Web Ontology Language (OWL). More specifically, we mapped two well-known drug class resources, Anatomical Therapeutic Chemical classification system (ATC) and National Drug File Reference Terminology (NDF-RT), as the pharmacological class backbone. Furthermore we extended the PCPO with individual clinical drug information extracted from RxNorm and Structured Product Labeling. In parallel, we calculated and compared chemical structure similarity for each drug pair from ATC and NDF-RT, and re-grouped drugs with a similar structure into a same drug class. PCPO will not only present big drug data into well-organized formal form, OWL with possible inference capability, but also potentially support computational drug repurposing application development.
AB - Dozens of drug terminologies and resources capture drug and/or drug class information; they range greatly in their coverage and their adequacy of representation. However, there are no transformative ways to link these resources together in a standard and formal fashion, which hinders data integration and data representation for supporting drug-related clinical and translational studies. In this study, we generated a standardized Pharmacological Class Profile Ontology, named PCPO, which integrates multiple drug resources in the Web Ontology Language (OWL). More specifically, we mapped two well-known drug class resources, Anatomical Therapeutic Chemical classification system (ATC) and National Drug File Reference Terminology (NDF-RT), as the pharmacological class backbone. Furthermore we extended the PCPO with individual clinical drug information extracted from RxNorm and Structured Product Labeling. In parallel, we calculated and compared chemical structure similarity for each drug pair from ATC and NDF-RT, and re-grouped drugs with a similar structure into a same drug class. PCPO will not only present big drug data into well-organized formal form, OWL with possible inference capability, but also potentially support computational drug repurposing application development.
KW - ATC
KW - NDF-RT
KW - Ontology
KW - Pharmacological class
KW - RxNorm
KW - SPL
KW - The Web Ontology Language (OWL)
UR - http://www.scopus.com/inward/record.url?scp=84921762811&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84921762811&partnerID=8YFLogxK
U2 - 10.1109/BigData.2014.7004397
DO - 10.1109/BigData.2014.7004397
M3 - Conference contribution
AN - SCOPUS:84921762811
T3 - Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014
SP - 77
EP - 84
BT - Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014
A2 - Lin, Jimmy
A2 - Pei, Jian
A2 - Hu, Xiaohua Tony
A2 - Chang, Wo
A2 - Nambiar, Raghunath
A2 - Aggarwal, Charu
A2 - Cercone, Nick
A2 - Honavar, Vasant
A2 - Huan, Jun
A2 - Mobasher, Bamshad
A2 - Pyne, Saumyadipta
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Big Data, IEEE Big Data 2014
Y2 - 27 October 2014 through 30 October 2014
ER -