TY - JOUR
T1 - Representing physiological processes and their participants with PhysioMaps
AU - Cook, Daniel L.
AU - Neal, Maxwell L.
AU - Hoehndorf, Robert
AU - Gkoutos, Georgios V.
AU - Gennari, John H.
N1 - Funding Information:
This work was partially funded by the VPH Network of excellence, EC FP7, project #248502.
Publisher Copyright:
© 2013 Cook et al; licensee BioMed Central Ltd.
PY - 2013/4/15
Y1 - 2013/4/15
N2 - Background: As the number and size of biological knowledge resources for physiology grows, researchers need improved tools for searching and integrating knowledge and physiological models. Unfortunately, current resources-databases, simulation models, and knowledge bases, for example-are only occasionally and idiosyncratically explicit about the semantics of the biological entities and processes that they describe. Results: We present a formal approach, based on the semantics of biophysics as represented in the Ontology of Physics for Biology, that divides physiological knowledge into three partitions: structural knowledge, process knowledge and biophysical knowledge. We then computationally integrate these partitions across multiple structural and biophysical domains as computable ontologies by which such knowledge can be archived, reused, and displayed. Our key result is the semi-automatic parsing of biosimulation model code into PhysioMaps that can be displayed and interrogated for qualitative responses to hypothetical perturbations. Conclusions: Strong, explicit semantics of biophysics can provide a formal, computational basis for integrating physiological knowledge in a manner that supports visualization of the physiological content of biosimulation models across spatial scales and biophysical domains.
AB - Background: As the number and size of biological knowledge resources for physiology grows, researchers need improved tools for searching and integrating knowledge and physiological models. Unfortunately, current resources-databases, simulation models, and knowledge bases, for example-are only occasionally and idiosyncratically explicit about the semantics of the biological entities and processes that they describe. Results: We present a formal approach, based on the semantics of biophysics as represented in the Ontology of Physics for Biology, that divides physiological knowledge into three partitions: structural knowledge, process knowledge and biophysical knowledge. We then computationally integrate these partitions across multiple structural and biophysical domains as computable ontologies by which such knowledge can be archived, reused, and displayed. Our key result is the semi-automatic parsing of biosimulation model code into PhysioMaps that can be displayed and interrogated for qualitative responses to hypothetical perturbations. Conclusions: Strong, explicit semantics of biophysics can provide a formal, computational basis for integrating physiological knowledge in a manner that supports visualization of the physiological content of biosimulation models across spatial scales and biophysical domains.
UR - http://www.scopus.com/inward/record.url?scp=84890902327&partnerID=8YFLogxK
U2 - 10.1186/2041-1480-4-S1-S2
DO - 10.1186/2041-1480-4-S1-S2
M3 - Article
AN - SCOPUS:84890902327
VL - 4
JO - Journal of Biomedical Semantics
JF - Journal of Biomedical Semantics
SN - 2041-1480
IS - 1
M1 - S2
ER -