Change - Systems Biology

Created on Feb. 13, 2013, 4:45 p.m. by Hevok & updated on April 26, 2013, 8:55 p.m. by Hevok

Systems Biology is an approach in which experimental biology is closely-integrated with mathematical or computational modeling in a synergistic way to answer biological questions that would be not be possible by empirical approaches alone. One of the goals of systems biology is to discover new emergent properties that may arise from studying the system as a whole, leading to more rapid and deeper understanding of how the system is controlled and how it responds to external stimuli. This level of understanding will greatly facilitate the future of biological systems. ¶
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aims to develop hypotheses based on integrated, or modelled data. ¶
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The ability to produce genome scale data for virtually every molecule class of an organisms provided one of the pillars of System Biology. ¶
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A systems biology project may be performed at a number of different biological scales or it may integrate across scales. ¶
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The system biological cycles is composed of modeling and experimentation. Models should be both descriptive and predictive [Antezana et al. 2013]. ¶
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Semantic Systems biology enables integrative biology via Semantic Web Technologies and includes integration of Ontologies into omics datasets, and development and application of innovative tools for working with semantically annotated large scale datasets, models and simulations. It includes the development and applications of terminologies and Ontologies for modeling simulations in computational biology and medicine. ¶
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The approaches comprises a cycle at which Experimentation leads to data generation. Information extraction techniques are used to Knowledge formalization into Knowledgebase. The knowledge base is undergoing consistency checking, querying, (Semi-)automated reasoning which leads to hypothesis formulation and experimental design [Antezana et al., Brief. in Bioinformatics 2009]. ¶