Ontological integration of data models for cell signaling pathways by defining a factor of causality called 'signal'.
Databases have collected masses of information concerning cell signaling pathways that includes information on pathways, molecular interactions as well as molecular complexes. However we have no general data model to represent comprehensive properties of cell signaling pathways, so that this type of information has been represented by two different data models that we call 'binary relation' and 'state transition'. The disagreement between the existing models derives from lack of consensus about a factor of causality in reactions in cell signaling pathways, which is often called 'signal'. We developed an ontology named CSNO (Cell Signaling Networks Ontology) based on device ontology. As device ontology is a research product of knowledge engineering, CSNO is the first application of it to biological knowledge. CSNO defines the factor of causality called 'signal', offers an integrative viewpoint for the two different data models, explicates intrinsic distinctions between signaling and metabolic pathways, and eliminates ambiguity from representation of complex molecules.
Takai-Igarashi
Takako
T
Computer Science, Graduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongou, Bunkyou-ku, Tokyo 113-0033, Japan. taka@bi.is.s.u-tokyo.ac.jp
Mizoguchi
Riichiro
R
D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D016208:Databases, Factual; D030541:Databases, Genetic; D008954:Models, Biological; D015398:Signal Transduction; D016212:Transforming Growth Factor beta / Q000378:metabolism
D016212:Transforming Growth Factor beta