Abstract
Systems computational modeling is the foundation of systems biology, which aims to describe and comprehend biological mechanisms. Structured formats can be used to encode model structures, molecular dynamics simulation parameters, and numerical results, but there is a growing demand for a semantic coating. The components of structured descriptions have significance thanks to contextual information, allowing them to be easily identified and interpreted. One of the most common techniques used for this is ontologies. Three ontologies that have been created expressly to fulfill the demands of systems biologists are presented. Systems Biology Ontology (SBO) provides semantic information about model elements. Data on existing simulation methods are available from Kinetic Simulation Algorithm Ontology (KiSAO), with characterization and interrelationships of systems biology frameworks. Dynamic characteristics of simulation findings and general system behavior are classified using the Terminology for the Description of Dynamics (TEDDY). Furthermore, adding contextual information to a model extends its life, making it easier to reuse. It may be utilized to make educated judgments about future simulation analysis by offering more important information about the biology of represented systems.
Publisher
Royal Society of Chemistry